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Review of access to essential services Financial inclusion and utilities An ippr report to the Equality and Human Rights Commission Kayte Lawton and Reg Platt September 2010 1 Contents About ippr About the authors Acknowledgements Executive summary 1. Introduction 2. Measures of financial exclusion 3. Financial exclusion among the equality groups 4. Measures of access to affordable utilities 5. Access to affordable utilities among the equality groups References Annex 1: Major household surveys used in this report Annex 2: Accounts identified in the Family Resources Survey Annex 3: The Wealth and Assets Survey 2 About ippr The Institute for Public Policy Research is the UK's leading progressive think tank, producing cutting-edge research and innovative policy ideas for a just, democratic and sustainable world. Since 1998, we have been at the forefront of progressive debate and policy making in the UK. Through our independent research and analysis we define new agendas for change and provide practical solutions to challenges across the full range of public policy issues. With offices in both London and Newcastle, we ensure our outlook is as broad-based as possible, while our Global Change programme extends our partnerships and influence beyond the UK, giving us a truly world-class reputation for high quality research. About the authors Kayte Lawton is a Research Fellow on the Citizens, Society and Economy programme at ippr. Reg Platt is a Researcher on the Citizens, Society and Economy programme at ippr. Acknowledgements The authors would like to thank Ellen Bloomer and Leo Ringer, both interns at ippr during this project, for their invaluable research support. Thanks to Glenn Gottfried at ippr for statistical advice and to Tony Dolphin at ippr and Anna Henry at the EHRC for comments on previous drafts. 3 Executive summary This report was commissioned by the Equality and Human Rights Commission to inform its first Triennial Review of inequalities and human rights in the UK. It provides evidence about inequalities and exclusion in access to financial services and affordable utilities. By law, individuals are protected from discrimination on the basis of particular characteristics, which are: gender, ethnicity, age, disability, sexuality, religion and belief, and transgender status. This report seeks to identify evidence of inequalities and exclusion experienced by individuals on the basis of these characteristics when accessing financial services and utilities. For each 'equality group', we provide statistical and other evidence about the extent of exclusion and inequalities, and how this plays out across the different equality groups. Where possible, we use evidence from national household surveys like the Family Resources Survey and the Living Costs and Food survey; where household surveys do not provide the necessary data, we draw on our sources, including quantitative and qualitative studies conducted by other researchers. Household surveys tend to lack information about sexuality, religion and belief, and transgender status, which makes it difficult to provide robust evidence about any exclusion experienced by different groups. In these cases, we have drawn primarily on qualitative sources, although there is often insufficient evidence to make any conclusions about the extent of inequality or exclusion. The report uses six measures of financial exclusion: ownership of a current account or other transactional bank account; savings; pensions; home contents insurance; access to affordable credit; and access to financial advice. Financial exclusion can have a negative impact on people's quality of life and the effects can include an inability to take part in day-to-day financial transactions; the inability to cope with unexpected events or planned lifestyle changes; and having to pay more for certain products and services The key issue for access to utilities is affordability, since provision is near universal in the UK. In this report, we look at differences in household expenditure on energy, water and telecommunications, as well as the take-up of internet services, among the equality groups. Financial services Gender Bank accounts There is no difference in the proportion of households headed by men and women who lack a bank account; and no difference in the proportion of individual men and women (approximately 4 per cent for both genders) who lack a bank account. 4 However, young men (aged 16 to 24) were more likely than young women to lack a bank account – 7 per cent compared to 5 per cent; women over 75 were less likely to have an account than men over 75. Savings and investments There are no major differences in the ownership of savings and investments between men and women – 40 per cent of men and 39 per cent of women had no formal savings in 2007/08; and the median value of savings held by men and women was identical, at £3,000. Using longitudinal datasets, researchers have found that life transitions appear to have a greater impact on women's savings than men's – after both divorce and parenthood, women saw a smaller increase in the value of their savings than men. Pensions Differences in private pension provision between men and women are primarily the result of different patterns of labour market participation, with women, on average, having lower employment rates, lower earnings, shorter working hours and more career breaks. In 2005/06, 43 per cent of men were contributing to a private pension, compared to 37 per cent of women. Even among men and women who are contributing to a private pension, the lower average earnings of women mean that their pensions will be worth less on average than men's. Insurance Men and women are equally likely to live in a household with no home contents insurance. Affordable credit Evidence from a range of services suggests that women are more likely to take on high-cost credit than men; this may be a function of the fact that women are more likely to be responsible for household finances, even in couple families, and that single women have lower average incomes. Ethnicity Bank accounts Among all ethnic minority groups, a greater proportion of adults lacked a bank account than White adults – 4 per cent of White adults had no bank account, compared to 11 per cent of people from a Pakistani or Bangladeshi background, and 6 per cent of both Indian and Black adults. Women from an Indian background were almost twice as likely to lack a bank account than Indian men; the difference between White men and women was very small; and it was not possible to calculate statistically significant estimates for differences between men and 5 women from Pakistani or Bangladeshi background or between Black men and women. However, researchers have found that ethnicity, gender and age are weak indicators of a household lack a bank account – regression analysis has shown that housing tenure and employment status are much more important. Savings Around half of adults Indian, Black and 'other' ethnic backgrounds had no formal savings in 2007/08 compared to a third of White people; 73 per cent of adults from Pakistani or Bangladeshi backgrounds have no formal savings. There are no significant differences in between men and women in each ethnic group in terms of owning formal savings. The median value of savings was lowest among Black adults, at £2,000 compared to £3,000 for White adults. Pensions Within each minority ethnic group, men and women were less likely than their White counterparts to have a private pension; just over 45 per cent of White males had a private pension in 2004/05 compared to just under a quarter of Black men and a fifth of Asian men. Women in each ethnic group were less likely than their male counterparts to have a private pension, except Black women – this may be because Black women are overrepresented in the public sector where private pension provision is widespread. Insurance Just over four out of five households headed by a White person had home contents insurance compared to 45 per cent of households headed by a Pakistani or Bangladeshi person, and 34 per cent of Black African households. Approximately two thirds of Black adults and adults from a Pakistani or Bangladeshi background who lack home contents insurance would like it but cannot afford it; this compares to half of White adults who lack insurance. Affordable credit There is little robust evidence about the use of affordable or high-cost credit, and financial advice, among different ethnic groups. Disability Bank accounts Adults who reported a disability or health condition that would be treated as a disability under the Disability Discrimination Act were more than twice as likely to have no bank account as those who did not – 7 per cent compared to 3 per cent, and meaning that almost half of adults without a bank account are disabled. 6 However, regression analysis has shown that people with a disability are slightly more likely to have an account once other factors (like income, housing tenure and employment status) have been taken into account. There were no major differences in account ownership between disabled men and women. Eleven per cent of adults with a learning difficulty or disability had no bank account – people with this kind of difficulty were the most likely to lack an account. Studies have found that people with a physical disability can have difficulties using facilities associated with bank accounts, which can reduce the benefits of account ownership. Savings and investments Half of people with a learning disability/difficulty had no savings, but there were no large differences in the ownership of savings between people with other kinds of disabilities and able-bodied people. The median value of savings held by disabled and non-disabled people was similar, at £3,200 and £3,000 respectively. There was no difference in the proportion of disabled men and women who lack savings. Pensions Research shows that there are no major differences in the private pension provision of disabled and non-disabled workers – the key difference for disabled people is that they are less likely to be in work. Although disability is dynamic, on average people who have a disability at some point in their life are less likely to be in employment, more likely to have lower earnings and more likely to retire early, all of which will reduce the likelihood of disabled people having a pension and the value of private pension savings. Insurance There is a small difference between the proportion of disabled and non- disabled adults who lack home contents insurance (23 per cent compared to 17 per cent); 14 per cent of people with a disability live in households that would like insurance but cannot afford it compared to 9 per cent of able-bodied adults. Almost a third of people with a learning disability or difficulty live in a household with contents insurance; among that group, two thirds would like insurance but cannot afford it, suggesting that affordability is the key challenge for learning disabled people. Affordable credit There is some limited evidence that disabled people are more likely to use high-cost credit; however, more research is needed to understand the extent to which this is driven by low income rather than disability. Age 7 Bank accounts Young adults (aged 16 to 24) are most likely to lack a bank account compared to other age groups – 6 per cent of young adults have no account compared to 4 per cent of adults in other age groups. Savings and investments Almost two thirds of young adults also lack formal savings compared to 27 per cent of adults aged 65 to 74; this is not unsurprisingly since the youngest age group has had little time to accumulate savings. There are no real differences in savings between men and women in the same age groups. Insurance Over half of both men and women aged 16 to 24 live in households with no home contents insurance; within that group roughly half would like insurance but cannot afford it. The proportion of men and women who live in households without insurance is much lower for older age groups and lowest among the 65 to 74 age group for both genders. Affordable credit Older people appear to be less comfortable with borrowing and less likely to take on credit, including high-cost credit However, it is not clear if this is an effect of age or a 'cohort effect', meaning that the use of credit will become more commons among older people over time; younger people will also have a greater need for credit because they have had less time to accumulate savings – it is not clear that there is are any problems with the different use of credit among different age groups. Other equality groups We have found no robust sources of data examining the extent of financial exclusion experienced by people of different sexualities, different religions or beliefs, and transgender people. There have been some small scale, qualitative studies but they have not included a comparator group so it is unclear whether any problems identified by these studies are unique to a particular equality group or experienced equally by the wider population. Affordable energy, water and telecommunications Gender There are no major differences in household expenditure on energy, water or telecommunications between households headed by men and by women, although we acknowledge that our measure of expenditure is imperfect. 8 Female-headed households are more likely to lack a mobile phone than male-headed households, but it is not clear that this is the source of any real inequality. Ethnicity There are no major differences in households expenditure on energy, water or telecommunications between households from different ethnic backgrounds, although we acknowledge that our measure of expenditure is imperfect. Asian households and those from 'other' ethnic backgrounds are more likely to live in energy inefficient homes, which may lead to higher energy spending in these households. There are no important differences in the take-up of different telecommunications services (fixed-line and mobile phones, and internet) among different ethnic groups. Age Household energy expenditure increases with age; this will in part be because of higher demand for energy services among older age groups. However, surveys also show that adults aged over 85 have a particularly high risk of living in a home with poor energy efficiency and of experiencing fuel poverty – this suggests that there may be an issue with the quality of housing in which over 85s live. Around four out of five people aged 16 to 64 have access to home internet, but this falls to 41 per cent for people aged 65 to 74, and 22 per cent for people aged 75 and over. Again, it is not clear whether the lower take-up of internet among older people is the result of age or cohort effects; nevertheless older people do seem to be missing out on the opportunities that home internet can bring and this is likely to continue for a number of years. Disability There is little reliable evidence about access to affordable energy and water services among disabled peopled, although existing surveys could be used to investigate further. People with a visual, hearing or mobility disability seem to be less likely to use home internet and mobile phones, and this group were also more likely than the rest of the population to lack internet because of problems with affordability. Research has also found that disabled people are much more likely than able-bodied people to have problems using communications services. 9 1. Introduction This report was commissioned by the Equality and Human Rights Commission to inform its first Triennial Review of inequalities and human rights in the UK. The report focuses on two interlinked policy areas, loosely brought together under the concept of access to essential services: financial exclusion and affordable utilities. We deal with each policy area in separate sections of the report and our focus is on providing statistical and other evidence about the extent of exclusion and inequalities, and how this plays out across the different equality groups. We recognise that this is not an exhaustive account of 'essential services'; we have focused on these two aspects because other policy areas have been considered separately by other work being done for the Triennial Review. Financial exclusion refers to the inability, difficulty or reluctance to access appropriate mainstream financial services (Mitton 2008). The effects can include an inability to take part in day-to-day financial transactions; the inability to cope with unexpected events or planned lifestyle changes; and having to pay more for certain products and services. Given the essentially universal provision of energy and water services in the UK, the central issue when it comes to equality in the utilities is cost and affordability. In recent years, the primary concern has been around fuel poverty and the serious negative effects this can have on the health and well-being of certain groups. However, there is less data available on the consumption of utilities by different equality groups, and it has tended to have less policy attention than financial exclusion in recent years. The drivers of exclusion and inequality can be similar for both financial exclusion and access to affordable utilities. Kempson and Whyley (2000) identify five key drivers of exclusion: Access: services are not accessible within a reasonable distance Condition: individuals are not eligible because of some individual circumstance, like a poor credit record Price: the cost of products or services relative to income excludes certain people Marketing: companies do not target particular people or areas, so individuals may not know about the availability of certain products and services Self-exclusion: this is sometimes legitimate, but sometimes based on assumptions about who should have products and services, or whether an individual would be eligible Data sources used in this report This report summarises the available evidence on financial exclusion and access to affordable utilities among seven of the protected equality groups: gender, ethnicity, age, disability, religion or belief, sexual orientation and transgender status. Our primary focus has been on collecting data from major household surveys, including those sponsored by government departments, academic institutions and the Office for National Statistics. These surveys 10 tend to have sufficient samples to be able to analyse exclusion and inequalities among those equality groups on which data is collected, although it is not always possible to generate very detailed data, for example, in inequalities between detailed ethnic groups or people with different forms of disability. Household surveys can also provide sufficient data to undertake some analysis of cross-sectional inequalities (where individuals belong to more than one 'protected group'), although there also limitations on the level of detail that can be achieved. Annex 1 outlines the major household surveys that we have drawn on. However, household surveys do not collect data on some of the equality groups, most notably religious belief, sexual orientation and transgender status. Some of our measures of exclusion, like access to affordable credit, are also difficult to assess using household survey data. Where it has not been possible to draw on household surveys with large sample sizes, we have used alternative sources, including polling and survey data, small scale studies and qualitative research. In each case, we explain where the evidence has come from, how large the sample is and, if possible, how representative or statistically robust the data is. Structure of the report The report presents our findings on financial exclusion first: chapter 2 explains our chosen indicators of financial exclusion and provides further background on aspects of financial inclusion policy. Chapter 3 summarises available data on financial exclusion among the seven equality groups. We then move on to look at access to affordable utilities, with chapter 4 setting the key measures and chapter 5 presenting our findings on access to affordable utilities among the equality groups. In the final chapter, we draw our findings together and explore some of the links between different forms of exclusion and inequality discussed in this report. 11 2. Measures of financial exclusion For the purposes of this report, we have chosen six areas of financial exclusion to focus on: transactional bank accounts; savings; pensions; insurance; affordable credit; and financial advice. In this section, we outline the indicators, explaining why they are important for understanding financial exclusion and how they can affect wellbeing. Transactional accounts One of the key measures of financial inclusion adopted over the last few decades has been whether an individual or household has a 'transactional' bank account – one that allows the user to carry out day-to-day financial transactions. Ownership of such accounts is generally regarded to be essential for full participation in modern British society, since they facilitate everyday activities that most people take for granted. Unlike most other measures of financial inclusion, there is no necessary relationship between ownership of a transactional bank account and income, although there is a clear correlation in practice (Financial Inclusion Taskforce 2009). Free banking is widely available in the UK so low income should not be a barrier to account ownership; and almost all adults have some form of income that could be paid into a bank account, meaning that almost everyone has a need for an account. This makes transactional accounts a particularly important measure of financial inclusion and explains why it has been the focus of so much policy attention in the field of financial inclusion. Transactional accounts include current accounts and basic bank accounts. Basic bank accounts were introduced in 2001 and allow the account owner to pay money in and make withdrawals at ATMs with a cash card, and pay bills by Direct Debit. Some accounts allow the use of a debit card but account owners cannot have a chequebook or an overdraft, and so are aimed at people on low incomes who do not want to risk going into debt; or people who may not be able to obtain a current account because of a poor credit rating. Post Office Card Accounts (POCAs) tend not to be regarded as full transactional accounts and this definition is followed in this report. POCAs only allow benefits, state pension and tax credits to be paid in, and cash can only be withdrawn over the counter at Post Offices or at Post Office ATMs. The POCA was introduced in 2003 when direct payments for state benefits were introduced, and were designed for people who did not want, or could not have, a basic bank account. In 2003, the government set a target to halve the number of adults living in households without a bank account. This was achieved in 2007/08, when the Treasury's Financial Inclusion Taskforce (FIT) reported that 0.89 million adults (just 2 per cent of all UK adults) lived in households that lacked a bank account, down from 2.0 million adults in 2002/03 (FIT 2009). However, this definition includes households that have some kind of savings or investment but may lack a transactional account. The FIT also found that 1.75 million 12 adults lived in households without a transactional account, down from 3.57 million in 2002/03 (Financial Inclusion Taskforce 2009). Households which have some form of savings or investments but lack a transactional account may still be experiencing some financial exclusion because they do not have an account that allows them to perform everyday financial transactions, like paying bills by Direct Debit. In the new analysis carried out for this report, we have identified individuals who are 'unbanked', because they have no account or investment of any kind (except perhaps a POCA); and those who lack a transactional account, but may have a savings account or investment. The FIT uses household-level data to assess account ownership, so that an adult is classed as 'banked' if they live in a household where at least one adult has an account, regardless of whether they themselves have an account. To some extent, the household-level is the right level of analysis because personal finances are normally conducted at the household level - for example, bills tend to be paid by one person on behalf of the household; the wages of one person are often used to support the needs of the whole household. However, simply looking at household-level data could gloss over inequalities between different individuals within households. There is a significant body of evidence to show that financial assets are not equally shared between male and female household members, for example (Westaway and McKay 2007). A focus on equality groups lends itself towards individual-level analysis rather than household-level. This is particularly true for gender, age and disability, but may be less relevant for ethnicity and religion or belief as these characteristics tend to be relatively homogenous within households. We therefore present new analysis of account ownership at the individual level in this report, using data from the Family Resources Survey 2007/08 (the source used by the FIT). Account ownership will provide few benefits if accounts are not used. A survey of 1,520 low-income consumers by the then National Consumer Council (NCC) found that over half of respondents with bank accounts still preferred to manage their money in cash (National Consumer Council 2005). Many respondents were also wary of paying bills by monthly Direct Debit, since they tended to budget on a weekly basis. This led the NCC to conclude that the provision of accounts to people on low incomes will not necessarily improve financial inclusion unless they are capable of meeting the particular needs of low-income consumers. However, we have not been able to identify any research which looks at account usage among the different equality groups. There is also some evidence to suggest that account ownership is not always associated with positive outcomes. The NCC survey found that low-income consumers with a bank account were more likely to be in arrears on household bills; and were more likely to have outstanding credit commitments. NCC researchers argued that this is because bank accounts reduce the ease 13 of cash-based budgeting and having a bank account makes it easier to access credit. These findings should be interpreted with care since the researchers did not control for other differences between 'banked' and 'unbanked' respondents which may have increased their susceptibility to debt or access to credit. However, they raise questions about the appropriateness of providing accounts to people on low-incomes, which were originally designed for people on higher incomes. Their suggestions for improving the flexibility and appropriateness of basic bank accounts include the availability of weekly Direct Debits; automated payments triggered by money entering the account; and payment systems that can incorporate occasional payment holidays. Savings Savings are vital for many families because they provide a cushion against dips in income or increased consumption needs, whether planned, like Christmas, or unplanned, like when a household appliance needs repairing. Savings, even of relatively small amounts, can help some families avoid debt or severe hardship (Lister 2006). A growing body of academic literature also suggests that savings can have wider benefits, including making people more willing (and able) to invest in their future and to take risks that have potentially high rewards (Bynner 2001; McKnight 2007; Sherraden 1991). This is sometimes referred to as the 'asset effect'. Unlike transactional accounts, savings and most other measures of financial inclusion are usually income-contingent – an individual has to have enough money to save (or to have been able to save in the past) in order to have savings. The main exception is where money has been inherited and kept as savings or investments1. Nonetheless, the link between income and ability to save means that there are clear reasons why a significant number of individuals may lack savings, particularly given the high levels of poverty in the UK. In this report, we have drawn on data from the Family Resources Survey (FRS) 2007/08 to provide information about (a) the ownership of savings and investments; and (b) the value of savings and investments. We focus on savings held by individuals, rather than households. We have included all the account types that the FRS gathers data on (listed in Annex 2), excluding current accounts, basic bank accounts and POCAs. FRS data only captures formal savings - those held with a recognised financial institution - and so misses any savings held in the home or left with family or friends. Some of this kind of saving is captured by the new Wealth and Assets Survey (WAS). Data in the WAS was not available for analysis at the time of writing, but we provide details of the data collected by the WAS in annex 3. 1 The other exception is the money contained in a Child Trust Fund, whereby government creates an endowment for all children regardless of income, which is accessible when the account owner turns 18. However, since this report only considers savings held by adults and CTFs were only introduced for children born from 2002, and have since been cancelled by the Coalition Government, CTFs do not feature in this report. 14 Pensions Pensions are fundamentally savings but we consider them separately in this report given the fact that they are a long term savings vehicle with limited, if any, access for the saver before they reach retirement age and that they are designed to provide an income in retirement. Pension policy has received substantial attention in recent years and has been the subject of much reform (see for example Great Britain 2008; Great Britain 2004). The UK pensions system currently has three basic elements (Pensions Policy Institute 2010a): The Basic State Pension (BSP) is a contributory system which people accrue an entitlement to by either paying National Insurance contributions if they are working or by receiving credits if not working due to childcare or other caring responsibilities (many more people are credited in now due to increased flexibility introduced in recent Pension Acts). An individual's BSP entitlement is calculated as they near State Pension Age (SPA) and can be supplemented by the means-tested benefit Pension Credit; State second pensions (known currently as S2P, previously SERPS) are also paid by the state (with entitlement again based on accrual) but unlike the BSP are linked to earnings and are not available to the self- employed2; Private pensions paid for by employers and individuals (Pensions Policy Institute 2010a). Broadly, there are two types of private pension: employer-sponsored schemes, usually occupational pension schemes; and personal pensions, which are organised by an individual and include stakeholder pensions. Wherever possible in this report, we look at the overall value of all private pensions held by individuals. In an attempt to encourage many more people to save into private pension schemes to enable them to better fund their retirement, the 2008 Pensions Act introduced a duty on employers automatically to enrol all eligible workers into a workplace pension scheme. This will (subject to a current review) start from 2012 (subject to staging and phasing in) and all employers will be expected to automatically enrol their employees into a pension scheme. If the employer does not currently offer a pension scheme to staff then they can enrol employees into a new scheme called the National Employment Savings Trust (NEST). This scheme is aimed at low to moderate earners unlike most other current pension provision and is designed to ensure that this group has access to a low-cost private pension scheme. Our primary focus in this report is the ownership of private pensions amongst the equality groups; the value of their contributions and the projected value of 2 The 2007 Pensions Act will make the State Second Pensions flat-rate rather than earnings- linked in future. 15 their pensions in retirement. The likelihood of people having a private pension and of it being of a value that will enable them to benefit from a decent pension income in retirement is clearly linked to labour market patterns, levels of employment, earnings and the age at which people retire and will therefore reflect the different patterns of employment and income among the different equality groups. Insurance Insurance can act in a similar way to savings, by helping to protect individuals and families against unforeseen shocks that might otherwise force people into debt or severe hardship. Because insurance is paid for directly, like savings but unlike transactional accounts, it is also linked to affordability and income. In this report, we focus on home contents insurance. This is partly because it is the one insurance product that all households could benefit from (whereas buildings insurance is normally only held by the owner of a property, so would not be relevant for renting households); and partly because there is the most reliable data about home contents insurance. Other forms of insurance, such as life insurance, can be important for some individuals and households but constraints of space, time and data mean that we focus here on home contents insurance. Data from both the FRS 2007/08 and the Living Costs and Food Survey (LCF) 2008 show that approximately one fifth of all UK households have no home contents insurance, with just over half of all low-income households having no cover (MacInnes, Kenway and Parekh 2009). Although insurance has been identified as a priority within financial inclusion policy, very little progress has been made over the last decade on increasing the proportion of households with contents insurance. Research by the FIT suggests that households are unlikely to lack insurance because they cannot find an insurance company willing to sell them a policy (FIT 2008). However, the same research also found that quotes for low-value contents were not always available, meaning that some households may find it difficult to obtain reasonably priced insurance. The study also found little evidence that areas with a high risk of flood, arson or crime were being systemically denied or priced out of insurance. Research by the Association of British Insurers (ABI) (2007) has also found that the design of home contents insurance may reduce their attractiveness to certain groups. Features including purchase through face-to-face contact, weekly premiums and payment of premiums in cash were popular among some, particularly those on a low income, but are often not available in practice. The ABI also surveyed 1,047 low and middle income households and found that only 1 per cent of respondents who lacked home contents insurance report being turned down for insurance (ABI 2007). Findings from the FIT and the ABI suggest that the main reasons why households do not have insurance are linked to affordability and financial capability, rather than explicitly exclusionary practices on the part of insurers. 16 Our primary analysis of home contents insurance draws on data from the FRS 2007/08 and the LCF 2008. The FRS includes a material deprivation question on home contents insurance, which asks households if they have insurance, and if they do not, whether this is because they do not want it or because they cannot afford it. The distinction between these latter two options may not be clear-cut because those households that say they do not want insurance may have decided they do not want it because they cannot afford it. Some individuals may also lack sufficient financial capability to make an informed judgement about the costs and benefits of not having insurance. We also use data from the LCF survey3 to estimate median expenditure on insurance as a proportion of total household expenditure. We recognise that this is an imperfect measure of the affordability of insurance and the extent to which particular groups might be paying more for insurance premiums than others. This is because it does not take into account differences in the value of insured possessions which might account for differences in premiums; and it is influenced by differences in household expenditure as well as the cost of insurance premiums4. Given the very small amount of household income that is spent on contents insurance (approximately 0.5 per cent of household income), even groups who appear to be paying more for insurance may not be significantly materially disadvantaged in practice. We look at insurance at the household level because insurance benefits everyone in the household regardless of who holds the policy. Affordable credit Credit acts like savings by allowing individuals and households to smooth out expenditure over time or cope with drops in income, helping families to avoid severe deprivation. Credit of some kind is usually available to most individuals but the cost of credit varies substantially depending on how it is accessed and how it is repaid, making affordability the key issue when looking at credit in the context of the equality groups. There is no standard definition of the affordability of credit. The APR associated with credit can be an important measure of affordability but just considering APR may not . Alternatively, assessing affordability by measuring repayments as a proportion of household income would not take into account interest rates, so a high-interest loan could be judged affordable even for a low-income household if it was being repaid in small weekly amounts over a long time-period. Both measures also fail to capture instances where individuals would like to access credit but are unable to because of the high cost. Low earnings, unemployment, unstable employment and a poor (or no) credit rating can make households a higher risk for lenders. Such households are 3 The LCF has a relatively small sample size of around 6,000 households, making detailed analysis of equality groups difficult, particularly for cross-sectional equality groups. Further in- depth analysis of LCF data could be achieved by adding data from two or more years' worth LCF surveys together in order to significantly boost the sample size. 4 See section 5 for a discussion of variations in household expenditure and the limitations of affordability measures based on household expenditure. 17 then more likely to face higher interest rates or be declined for credit by mainstream lenders – high street banks, credit card companies and personal loan firms. Households that lack a bank account are also very unlikely to be accepted for credit by a mainstream lender. People who are unable to access credit through mainstream channels may be able to access credit through a number of other channels: Commercial lenders who offer the same products as high street providers, such as personal loans, but at much higher interest rates. Commercial lenders who offer 'alternative' credit products designed specifically for the needs of low-income borrowers. These types of products include home credit or doorstep lending; pawnbrokers; sale and buyback shops; payday loans; mail order catalogues; and rental purchase schemes. The typical APR for these products can be very high, commonly over 100 per cent. Research conducted for the FIT (2010x) found that the largest source of non-standard credit among low-income households was home credit, which provided loans valued at approximately £1.5 billion and a typical APR of between 275 and 500 per cent. Pawnbrokers accounted for the second largest share of the market with a typical APR of 100 per cent. Illegal moneylenders, i.e. providers operating without a credit licence Third sector lenders, including credit unions and community development finance initiatives. Support for third sector lending has been the primary focus of government efforts to improve access to affordable credit, and the government has provided £100m for a Growth Fund to boost lending by credit unions and Community Development Financial Institutions (CDFIs). The Social Fund, which provides interest-free Budgeting Loans to people in receipt of state benefits. The inadequacies of the Social Fund are well documented and demand far outstrips supply (Collard and Kempson 2005), meaning that the Social Fund is completely incapable of meeting the needs of all low-income households requiring affordable credit. Family and friends, which Collard and Kempson (2005) suggest is a relatively common source of borrowing among low-income families, although they do not provide any statistics on the proportion of families who use this source of credit (Collard and Kempson 2005). Informal savings and loans clubs, run by groups of friends, relatives or colleagues. Research suggests that the design of credit products is very important for some households. Low-income households tend to budget weekly and so prefer to repay loans weekly; prefer to pay in cash; and like having the flexibility to miss payments in some weeks and catch up the week after (Whyley 2000). Alternative credit products can be attractive because they offer these terms, and this can be more important than the APR or overall cost of borrowing – in fact, these requirements often mean that costs are higher, and it can be difficult to ascertain the extent to which providers are charging legitimately higher charges. There are also issues with competition, 18 transparency and lending terms which might mean that low-income consumers are being charged more than is necessary to meet the extra costs of their preferred form of borrowing (Whyley and Brooker 2004). Given the definitional issues around affordable credit, it is perhaps not surprising that there are no large-scale datasets which provide a specific measure of the availability or take-up of affordable credit among different types of households. There is a particular lack of systematic large-scale data on users of alternative credit products: some estimates put the number of users of alternative credit at around 3 million, although some researchers believe this may be an overestimation (HM Treasury 2004; Whyley and Brooker 2004). In this report, we have looked at the types and costs of credit people are accessing and made some assumptions about its affordability. Financial advice Financial advice, which includes but goes beyond debt advice, can be vital in helping people manage their finances, ensuring they receive the maximum return from savings and investments and are able to avoid or cope with financial difficulties. Like many other measures of financial inclusion, access to financial advice is often dependent on income. People with sufficiently large incomes are usually able to access advice from commercial providers that is either free at the point of delivery (but is in fact paid for indirectly through commissions and higher arrangement fees) or affordable relative to their incomes, primarily on the basis of their 'buying power' within the financial services market. Commercial providers have very little to gain from advising low-income consumers, so most people on low incomes rely on free advice services provided by the third sector. Research suggests that there is sufficient unmet demand for financial advice among households who cannot pay for it. A 2004 study for the Treasury estimated that third sector financial advice was available for around 600,000 people each year, while demand was around 850,000 (HM Treasury 2004). A study by Friends Provident Foundation found that there were approximately 500,000 people whose need for debt advice was not being met (Financial Inclusion Taskforce 2010). The 2008/09 recession increased demand for financial advice, with the FIT predicting that it will take around three years for demand for debt advice to return to pre-recessionary levels (Financial Inclusion Taskforce 2010). Following the Thorensen Review of Generic Financial Advice, the government is currently piloting a generic face-to-face advice service called Money Guidance, which will be rolled out nationally from 2010. This should help to reduce some of the issues face by excluded groups in accessing free financial advice, although it will have to be monitored to ensure it is reaching people from the different equality groups. There is very little statistical information to draw on about the provision of financial advice and how this relates to the equality groups. In this report, we have drawn primarily on qualitative sources. 19 Practical reasons for exclusion Despite the many benefits of financial inclusion, there are practical reasons that could explain some of the inequalities in financial inclusion between different equality groups. These reasons could go some way to explaining why certain people are more likely to lack particular products and services. They include: Adults with some types of learning difficulty or disability, serious mental health problems, terminal illness or addiction problems. Their condition may make them temporarily or permanently unable to manage their own finances, and allowing them to do so could put them at extra risk. However, this does not necessarily mean that it is acceptable for such individuals to be completely financially excluded, simply that they may not be able to use particular products and services. For example, it may not be practical for them to have a bank account but there is no reason in theory why they should have to live in a household that has no home contents insurance. People who have an undischarged bankruptcy or a record of fraud. This will apply to a minority of people only. Again, individuals in this group may not be able to hold certain products personally but this does not legitimise their complete exclusion from all products and services. A larger number of people may experience difficulties accessing financial services because of a poor credit record, although there is no clear-cut way of deciding if this is 'legitimate' or not. Individuals who have made a rational and informed decision not to access a particular product or service. In the evidence we present in this report, it is very difficult to ascertain the extent to which genuine and informed free choice is driving exclusion and inequality. The patterns of inequality and exclusion that we uncover in this report suggest that the primary drivers are related to factors like income, discrimination and education; however, legitimate self-exclusion cannot be ruled out. 20 3. Financial exclusion among the equality groups Having set out our six measures of financial exclusion, in this section we discuss the findings of our research and analysis of the extent of financial exclusion among the protected equality groups. Our focus is on quantitative data collected through major national surveys, providing robust evidence of the extent and nature of inequality. However, where such data is not available we draw on alternative sources, including qualitative sources, to give a picture of financial exclusion among the equality groups. This is particularly important for the equality groups which do not feature in major household surveys, primarily religion, sexuality and transgender status. As outlined above, there are also aspects of financial exclusion that are not easy to measure in numerical terms, and we draw on smaller scale or qualitative studies to assess inequalities in these aspects. This section is structured around the seven protected equality groups. Gender Current accounts The Treasury's Financial Inclusion Taskforce (FIT) produces its own statistical analysis of which kinds of people are more likely to lack access to a bank account. FIT analysis of FRS data found that, in 2007/08, the gender split of head of households among households without a bank account was almost identical5. This represents a significant change from the baseline year of 2002/03, when 66 per cent of households lacking a bank account were headed by women. This suggests that at least some of the efforts to reduce this kind of financial exclusion have been directed at households headed by women. This is supported by data from the FIT that shows that the proportion of 'unbanked' households which are lone parent households has fallen, compared to a rise among single-person households and no real change among couple households (Financial Inclusion Taskforce 2009). One explanation could be the introduction of Direct Payments for state benefits, which disproportionately affected lone parents, since the majority are in receipt of some form of state benefit or tax credit. We have carried out our own analysis using data from the Family Resources Survey6 to look at differences in account ownership between men and women at the individual level. Figure x shows the proportion of adults who are 'banked', 'unbanked' and who lack a transactional account (but do have a savings account of some kind) Figure x shows no major differences between men and women. We estimate that 887,000 men were 'unbanked' (had no account of any kind) in 2007/08, as were 979,000 women. Women are slightly 5 Gender is the only equality group included in the FIT's annual report so we have not been able to draw on the reports for analysis of other equality groups. 6 Data analysis of financial exclusion using household survey data assumes that such surveys are capable of generating sufficient responses among individuals and households who are likely to experience exclusion. The FRS employs a robust sample design and selection procedure and we have not identified any concerns about the representativeness of FRS data on exclusion in the literature on financial exclusion, including studies of financial exclusion utilising FRS data by academics in this field. 21 more likely to have some form of saving or investment, but no transactional account. Figure x: Proportion of adults who are 'banked', 'unbanked' or lack a transactional account, by gender (2007/08) 100 Male 80 Female % of adults 60 40 20 0 Unbanked No transactional Banked account Source: Authors' calculations using Family Resources Survey 2007/08 Notes: Unbanked refers to adults who do not have an account of any kind. This will include some adults who only have a Post Office Card Account, since ownership of a POCA alone does not qualify as a full bank account in the financial exclusion literature. A transactional account is a current account or a Basic Bank Account. Banked adults are those who have at least one current account or Basic Bank Account. The chart excludes respondents who did not know if they had an account or refused to answer the relevant question. Although there is no significant difference in the risk of being 'unbanked' between men and women, this risk does differ between the genders when the data is disaggregated by age. Figure x shows that among both men and women, young people (adults aged 16 to 24) were most likely to be 'unbanked', but the risk is much higher for young men – 7.4 per cent compared to 5.2 per cent for young women. This translates into 222,000 young men and 148,000 young women lacking an account in the UK. Furthermore, across the age groups, the risk of being 'unbanked' is fairly steady for men over the age of 25, whereas it increases slightly for older women (those over 65). This, plus the fact that women tend to live longer, means that there are 127,000 women aged 75 and over who are 'unbanked' (5.0 per cent of all women in that age group) compared to 57,000 men (3.8 per cent) in the same age group. 22 Figure x: 'Unbanked' adults by age and gender, 2007/08 9 8 Male Female 7 % of adults 6 5 4 3 2 1 0 4 4 4 4 4 4 + -2 -3 -4 -5 -6 -7 75 16 25 35 45 55 65 Source: Authors' calculations using Family Resources Survey 2007/08 Notes: Differences between men and women within each age group are significant at the 5 per cent level only for the 16-24 and 75+ age groups. As discussed above, an individual without a bank account may not be completely financially excluded if they live with other adults who do have an account. For this reason, we wanted to look at whether the individuals who we have identified as 'unbanked' do live in 'banked' households. Using FRS household date, we found that only 11 per cent of adults without a transactional account also live in a household where no other adult has an account capable of accepting Direct Debit payments. This represents approximately 314,000 adults, a small but important group. These adults are likely to be experiencing very severe financial exclusion as they have no access to a transactional account within their household, although they may be able to access banking services through accounts held by friends or family outside the households. Our analysis found that 12.6 per cent of 'unbanked' men (162,000) do not have access to a transactional account within the household, compared to 9.9 per cent of women (152,000). Savings and investments FRS data for 2007/08 shows no significant differences in the ownership of savings and investments between men and women. We found 40 per cent of adult men and 39 per cent of adult women had no savings, equivalent to 8.7 million and 9.0 million individuals respectively. Among adults who held any savings (i.e. excluding those with no savings, including those who had savings account but no savings), the median value of savings held by men and women was identical, at £3,000, and figure x shows the value of savings and investments follow a similar distribution for men and women. 23 Figure x: Distribution of the value of savings and investments held by men, 2007/08 20 15 10 5 0 0 10000 20000 30000 40000 Total value of savings and investments (£) Source: Authors' calculations using Family Resources Survey 2007/08. Notes: Excludes respondents with no savings or savings above £50,000, and those who did not provide a value for savings and investments held. Figure x: Distribution of the value of savings and investments held by women, 2007/08 24 20 15 10 5 0 0 10000 20000 30000 40000 Total value of savings and investments (£) Source: Authors' calculations using Family Resources Survey 2007/08. Notes: Excludes respondents with no savings or savings above £50,000, and those who did not provide a value for savings and investments held. Using data from the British Household Panel Survey (BHPS) 2005/06, Westaway and McKay (2007) found that 44 per cent of men were currently saving from their income, compared to 40 per cent of women. The same study also found a significant difference in the median value of men's and women's savings - £5,000 for men and £3,000 for women. This contrasts with our findings from analysis of FRS data. It is not clear what explains this striking difference between the results of the two pieces of analysis, beyond the different sample sizes in each survey (the BHPS is much smaller) and the different years' data analysed. Westaway and McKay (2007) also found that men are more likely to invest in high risk/high return products like shares and unit trusts. FRS data only allows us to look at savings held by men and women at one point in time. Using longitudinal data from the BHPS, Westaway and McKay (2007) looked at what happened to men's and women's savings over a 10 year time period. This analysis found that men who were married in 1995 had experienced a similar increase in the value of their savings and investments regardless of whether they divorced or stayed married. However, women who divorced during this time-period saw a much smaller increase in the value of their savings compared to women who stayed married. This is likely to be because women, particularly lone parents, have lower average incomes compared to men. The researchers found a similar pattern for women who became parents for the first time; and also for the amount of debt that women had. They conclude that life transitions have a much more significant (and negative) impact on women's savings than men's. 25 Pensions Pensions have long been a source of substantial gender inequality, primarily because the pensions system has historically been designed to meet the needs of single breadwinner couples who stay together throughout retirement (Ginn 2003; Arber, Davidson and Ginn 2003). When men's and women's lifestyles have diverged from this model, women have tended to lose out financially. Although this report is concerned primarily with inequalities in private pensions, it is worth providing some context by looking at the status of women in the state pension system. Table x shows the proportion of men and women reaching State Pension Age (SPA) who are or will be entitled to less than the full Basic State Pension (BSP). Table x: Proportion of adults reaching state pension age entitled to less than full Basic State Pension Proportion of people reaching state pension age who are entitled to less than the full Basic State Pension 2008 2010 2025 2050 Men 10% 5% 5% 10% Women 60% 25% 5% 10% Source: Pensions Policy Institute (2010b) Notes: Projections take into account changes introduced in the Pensions Act 2007. The increase in the proportion of adults entitled to the full BSP between 2025 and 2050 may be a result of the increase in the State Pension Age, which was due to increase from 65 to 68 between 2024 and 2046 when these figures were calculated. Figures are rounded to the nearest 5%. An individual is entitled to less than the full BSP if they have not accrued enough 'qualifying years' during their working-age life, for example, if they have not been in work or seeking work, for example, because of caring responsibilities. Historically, this has been much more common for women than men because of their traditional caring role in the family. Reforms introduced in 2007 Pensions Act were designed to reduce the number of qualifying years required by both men and women before they are entitled to the full BSP. However, table x shows the differential entitlement to the full BSP between men and women is not expected to equalise until 2025, meaning that women reaching the SPA will continue to have a significant risk of less than full entitlement to the BSP. Data from the Pensions Policy Institute shows that a similar proportion of men and women were accruing entitlements to the State Second Pension (or equivalent) in 2006/07. Table x shows that around 30 per cent of both men and women were not accruing entitlements. These figures suggest that, in future, the State Second Pension (S2P) entitlement of men and women will be fairly equal as the payment gradually becomes a flat rate one rather than being linked to earnings. However, before S2P payments become flat rate, and although similar proportions of men and women are accruing entitlement to S2P, the average value of contributions and therefore potential income in 26 retirement will continue to be lower for women than for men. This is due to women's lower average earnings. Table x: Proportion of working-age adults accruing entitlements to S2P or contracted-out equivalent (2006/07) Proportion of working age adults Contributing Credited-in Not qualifying Men 62% 8% 30% Women 55% 15% 30% Source: Pensions Policy Institute (2010c) Private pensions are the generic term for all pensions that are not provided by the state and include occupational pensions and other pensions provided by employers; and stakeholder pensions and other pensions arranged by individuals, often those who are self-employed. Unlike contributions to state pensions, membership of private pensions is voluntary. FRS data for 2005/06 shows that 43 per cent of men were contributing to a private pension compared to 37 per cent of women (Office for National Statistics 2010a)7. This gap had narrowed slightly over the preceding five years, with a six percentage point fall in the proportion of men who were contributing to a private pension between 1999/00 and 2005/06 but almost no change for women (ONS 2010a). Although this shows some trend towards equalisation between men and women, it is not happening as a result of an upward trend for both men and women. Women's lower participation in private pension provision is influenced by their lower employment rate; their greater propensity to take career breaks; and their lower average earnings, meaning they are less likely to be able to afford to contribute to a private pension even if one is provided by their employer (Steventon and Sanchez 2008). As Westaway and McKay (2007) point out, when women and men are eligible for an employer pension scheme, a very similar proportion (around 70 per cent) opt in, suggesting that the differential take-up of private pensions is not down to different preferences between men and women. Data from the General Lifestyle Survey 2008 confirms the differences in private pension provision between full-time and part-time employees. The survey found that almost identical proportions of male and female full-time employees had a private pension - 64 and 63 per cent respectively (Office for National Statistics 2010x). In contrast, only 44 per cent of part-time female employees had a private pension (estimates are not available for part-time men due to small sample sizes). Among female employees, 42 per cent work part-time (Office for National Statistics 2010b). Even among men and women who are contributing to a private pension, there will nevertheless be a significant difference in the value of their contribution, 7 Pension estimates from the FRS have not been issued since 2005/06 due to data issues and we have therefore not drawn heavily on FRS pensions data in this report. ONS expects revised pensions data from the FRS to be available in the 2009/10 dataset. 27 since women earn significantly less on average than men and contributions are typically based on a percentage of salary. Men's gross median weekly earnings were £491 in 2009 compared to £310 for women (Office for National Statistics 2010c). This will translate into a lower average value of private pensions held by women. However, women's overrepresentation in the public sector may help to increase the average value of women's private pensions, since pension provision tends to be much better in the public sector than the private sector. According to the TUC, for example, women hold approximately two thirds of all Defined Benefit pensions8 in the public sector (TUC 2010). However, it is important to note that many women working in the public sector with a DB pension will be on relatively low-wages and often working part-time. This means that even where women in the public sector have a DB pension, the value of that pension (and subsequent retirement income) is likely to be lower than those held by men. FRS data also suggest that women and men are equally likely to be accruing a private pension up to the age of around 30. Figure x shows that between the ages of 30 and the State Pension Age, a gap of between 5 and 10 percentage points opens up between men and women in terms of private pension accrual. 60 50 Men 40 Women 30 20 10 0 9 9 9 9 PA -1 -2 -3 -4 -S 16 20 30 40 50 Source: Pensions Policy Institute (2010d) Note: Based on data from the FRS 2005/06 Other data suggests that younger women are actually more likely than their male counterparts to contribute to a private pension. BHPS data shows that 67 per cent of women aged 25 to 29 who are eligible to join their employer's pension scheme do so, compared to 57 per cent of men in the same age group (Westaway and McKay 2007). FRS data shows that childless women under the age of 40 are more likely than their male counterparts to have a private pension (Westaway and McKay 2007). The implication is that once 8 In a Defined Benefit pension, the amount of income received in retirement is defined in advance by reference to length of service and final salary. This contrasts with a Defined Contribution pension where retirement income is determined by the performance of the pension fund. Defined Benefit schemes are generally more generous. 28 women become parents they are much more likely than men to stop contributing to a private pension. The lower likelihood of a woman being a member of a private pension scheme at any point in their working-age life and the lower average value of their contributions over their working life, means that women receive significantly lower retirement income from private pensions. Analysis of FRS 2004/05 data has found that single male pensioners receive an average £85 a week in private pension income compared to £48 a week for single female pensioners. Some of this income will include widows' pensions, that is, it will be the result of pension rights accrued by men rather than directly by women. (Westaway and McKay 2007). Insurance Analysis of FRS data shows that men and women are equally likely to live in a household with no contents insurance, as figure x shows. Women are slightly more likely to say that they live in a household which would like insurance but cannot afford it. Analysis of the LCF expenditure data finds that female- headed households spend 0.8 per cent of total expenditure on home contents insurance compared to 0.6 per cent among male-headed households. Any difference in expenditure on insurance will reflect in part differences in overall household expenditure, with female-headed households having lower overall expenditure (see section 5 for details). Figure x: Likelihood of men and women living in households with home contents insurance, 2007/08 100% 80% % of adults 60% 40% 20% 0% Men Women Does the household have contents insurance? Yes Would like to but can't af f ord Doesn't want Source: Authors' calculations using Family Resources Survey 2007/08 Affordable credit As we have already discussed, there is no single definition of affordable credit so we must draw on different sources of information to understand the borrowing habits of different groups, and make judgements about what this could say about their access to affordable credit. One way of doing this is to look at use of alternative forms of credit. Although alternative credit is not automatically unaffordable, they are associated with higher costs, including typical APRs of between 200 and 500 per cent (Collard 29 and Kempson 2005; Kempson et al 2009). Figure x shows few differences in the type of credit taken on by men and women – except that men are more likely to have a personal loan and women are much more likely to access credit through mail order companies, which tend to have much higher APRs than mainstream lenders (Collard and Kempson 2005). Ten per cent of women used this form of credit in 2005/06 compared to just two per cent of men. Figure x: Ownership of different types of credit by gender, 2005/06 25 Men 20 Women % of adults 15 10 5 0 ft er se an d n rd s ra oa nd un rd ca ha lo rd tl rie lo lF ve al rc it en ed /f ai cia on pu O ud /m Cr ily rs So re St Pe m e Hi Fa gu lo ta Ca Source: Westaway and McKay (2007) Note: Uses data from British Household Panel Survey 2005/06 Figure x only provides data on one form of alternative credit (which is likely to be high-cost). However, the pattern of women being more likely to take on alternative and potentially high-cost credit is supported by polling and survey data that asks about other forms of credit: A 2006 survey of 2,805 low-income individuals in 18 areas of the UK conducted for the FIT found that 22 per cent of women were using both 'mainstream'9 and 'high-cost'10 credit, compared to 18 per cent of men; and 24 per cent of women were using only high-cost credit compared to 14 per cent of men (Financial Inclusion Taskforce 2007). A 2004 Mori poll of 2,400 home credit users conducted on behalf of the then National Consumer Council estimated that women accounted for 65 per cent of customers in the home credit market (Whyley and Brooker 2004). 9 Defined as credit cards from banks and building societies, agreed overdraft facilities, personal loans from banks and building societies, store cards, hire-purchase agreements and secured loan. 10 Defined as mail order, home credit, non-bank credit cards, hire-purchase from retail shops, buy-back shops, pawnbrokers, payday loans and unlicensed lenders. 30 A Citizens Advice survey of 924 clients who had sought debt advice from the charity found that 4 per cent of female respondents had problem debt with home credit companies, compared to 1 per cent of men; and that 15 per cent of female clients had debt with a mail order company compared to 4 per cent of men (Edwards 2003). Collard and Kempson (2003) found that women are more likely to use pawnbrokers. Women may turn to alternative and high-cost lending because they are unable to access mainstream credit. The data on gender differences in the take-up of personal loans in figure x may provide some support for this. Alternative credit products have certain design features (discussed above), which may also be more appealing to women. Researchers have also suggested that women are more likely to use home credit and mail order partly because of the home-based delivery and it may be that home credit is particularly appealing to women who are not in formal employment and spend time at home, such as women with poor health or caring responsibilities (Collard and Kempson 2005). The higher use of high-cost lending among women may also reflect the fact that in couple households women are more likely to take responsibility for household finances, and therefore more likely to be the one to draw on alternative sources of credit to balance household finances. Most providers of alternative credit act entirely legally and often provide a useful service to people who would otherwise be unable to access credit, and may suffer serious hardship as a result (Kempson, Ellison, Whyley and Jones 2009). However, some communities are also targeted by illegal moneylenders and there is evidence from the government's pilot schemes designed to help people avoid illegal lenders, that women are more likely than men to use illegal moneylenders as well. However, it should be noted that this view is based on relatively small-scale studies and witness statements (Policis and Personal Finance Research Centre 2006; HM Treasury 2007). The overrepresentation of women among users of alternative credit suggests a significant demand for alternative and affordable credit among women, particularly those on low incomes. For example, the Treasury found that over 70 per cent of loans made through its Growth Fund, which provides funding to third sector lenders, had been made to women (HM Treasury 2007). 31 Ethnic origin Transactional accounts The prevalence of account ownership among adults from different ethnic backgrounds is revealed in figure x, which shows that people identifying as White are the group most likely to be banked – just 4 per cent had no account, although this does translate into 1.55 million adults. Adults from all ethnic minority backgrounds had an above-average risk of being 'unbanked'. This was strongest among adults from a Pakistani or Bangladeshi background, with over 11 per cent of this group lacking a transactional account - 85,000 adults. This compares with 6 per cent of adults from an Indian background and 6 per cent of people identifying as Black. Black people and those from a Pakistani or Bangladeshi background were also more likely than average to have some form of savings or investments but to lack a transactional account. Figure x: Proportion of adults who are unbanked, banked and lack a transactional account by broad ethnic group, 2007/08 100 White 80 Indian Pakistani & Bangladeshi Black % of adults 60 Other 40 20 0 Unbanked No transactional Banked account Source: Authors' calculations using Family Resources Survey 2007/08 Notes: Unweighted sample sizes: White = 38,684; Indian = 651; Pakistani/Bangladeshi = 566; Black = 750; Other = 1,191. Excludes respondents whose banking status was recorded as unknown. When testing the cross-tabulation between ethnicity and bank status, p-value < 0.001. Analysis for more detailed ethnic groups is not possible due to small sample sizes. Table x shows that women from an Indian background are almost twice as likely as their male counterparts to lack a bank account. There is only a very small difference between the proportion of White men and women who lack an account, while it was not possible to calculate statistically significant estimates for the difference in account ownership between men and women from Pakistani or Bangladeshi backgrounds, or between Black men and women. 32 Table x: Proportion of adults without a bank account (unbanked), by gender and ethnicity, 2007/08 % with no account Ethnic group Men Women White* 3.8 3.7 Indian* 4.8 8.1 Pakistani/Bangladeshi 9.5 13.7 Black 6.1 5.4 Other* 5.3 9.1 Source: Authors calculations using Family Resources Survey 2007/08 Notes: Gender differences between ethnic groups marked * are statistically significant at the 5% level. Finney and Kempson (2009) carried out regression analysis of the factors related to not having a bank account, using data from the FRS 2006/07. Their analysis found that Pakistani or Bangladeshi households were 4.5 times more likely than White households to lack a bank account, once other factors had been taken into account. Black people were 2.4 times more likely than White households to be unbanked; results for Indian and 'Other' households were not statistically significant once other factors had been taken into account. However, ethnicity (and in fact all other equality characteristics measured in the FRS) was only a weak indicator of a household lacking a bank account. Other factors, primarily having a POCA, housing tenure or employment status, were much more important (Finney and Kempson 2009). Using evidence collected from 35 semi-structured interviews, Mawhinney (2010) found that some respondents from ethnic minority backgrounds did not use banks because they did not trust them, either perceiving them to be acting in their own interests and not in the interests of their customers, or perceiving them to be incompetent. However, it is not clear how these sentiments are particular to or vary between different ethnic groups. Khan (2008) also suggests that account ownership among some ethnic minority groups may be lower because individuals are more likely to have their wages paid in cash and on an informal or irregular basis. This was thought to affect Chinese and Bangladeshi people working in sectors like taxi driving and catering, and in family-owned businesses. The 2009 Runnymede Money Survey asked 110 respondents to what degree they agreed with the statement: 'In general, I have a lot of trust and confidence in high street financial institutions'. Among White British respondents, 76 per cent disagreed; 58 per cent of non-White British disagreed; and 62 per cent of respondents from a Black Caribbean background disagreed (Mawhinney 2010). However, these results derive from a very small sample size, making it impossible to draw any concrete conclusions. Mawhinney (2010) also found that recent migrants and older people from ethnic minority backgrounds experienced particular difficulties in navigating 33 banks and other institutions. Some interviewees in the research did report instances of feeling discriminated against by banks, which Mawhinney suggests is more likely to be due to the behaviour of an individual bank staff member rather than something that is institutionalised within the bank. Mawhinney (2010) also found that a minority of interviewees had chosen to go to banks that speak a particular non-English language, although this may not always be a viable option for all individuals. Khan and Simpson (2009) found that BME groups are likely to live in areas without access to free cash machines or with lower than average numbers of them. By examining the placement and cost of 64,807 cash machines, the researchers estimated that if people living in these areas always used their nearest fee-charging machine they would pay an extra £120 pounds per year in charges. They estimated that BME people are paying £14.50 more per annum to access cash than White British people. Savings and investments Large differences in the ownership of savings and investments were identified across broad ethnic minorities. Most notably, individuals in all the broad ethnic minority categories were less likely than White people to have savings, as figure x shows. Savings ownership is similar among people from Indian, Black and 'Other' ethnic backgrounds, with around half of adults from these ethnic groups having no formal savings, compared to 36 per cent of White people. People from a Pakistani or Bangladeshi background are particularly likely to lack savings – 73 per cent have no formal savings. It should be noted that these results do not control for income, which is known to be lowest among Pakistani and Bangladeshi households (Department for Work and Pensions 2009). Figure x also shows that there are no significant differences between men and women in terms of having formal savings within each ethnic group. This is in contrast to the differences in current account ownership identified previously between Indian, Pakistani and Bangladeshi men and women. This finding is supported by Westaway and McKay (2007), who found little difference in the proportion of men and women with savings within each ethnic group, drawing on earlier FRS data. Figure x: Proportion of adults who do not have formal savings, by ethnic group (2007/08) 34 80 70 Male 60 Female % of adults 50 40 30 20 10 0 te n er n k Ba ac ia hi th d W Bl O k/ In Pa Source: Authors' calculations using Family Resources Survey 2007/08 Notes: There are no statistically differences between genders within each ethnic group. FRS data also shows that White people are more likely than some ethnic minority groups to have a broader range of savings and investment products. Table x shows that a significant proportion of White people have savings accounts, ISAs, Premium Bonds, and stocks and shares, whereas very few people from Pakistani and Bangladeshi backgrounds have savings other than standard savings accounts. This is also true to a lesser extent for Black people. However, people from an Indian background have, on average, a much broader portfolio than other minority groups, although they are still less likely than White people to have each kind of saving and investment product. Table x: Proportion of households holding different types of savings and investment products, by ethnicity of head (2005/06 – 2007/08) Ethnicity Saving / investment Pakistani / product White Indian Black Mixed Other Bangladeshi Bank or building society savings 50 41 26 38 40 39 account ISA 37 30 8 17 26 23 Premium Bonds 24 11 5 7 15 10 Stocks & shares 20 17 6 8 11 14 PEPs 6 5 1 2 3 3 35 Unit Trust 5 2 - 1 4 3 National Savings 3 3 0 1 2 2 bonds Sample size 73,447 1,055 848 1,579 511 981 Source: Department for Work and Pensions (2009b) Notes: Figures are combine data from 2005/06, 2006/07 and 2007/08 to generate large sample sizes; and are for selected account types only. We have also used FRS data to analyse the value of savings held by adults from different ethnic background, highlighted in figure x. Although people from an Indian background are less likely than White people to have savings, when they do have savings, their median value is almost identical to the value of savings held by White people, at £3,000. However, adults from other minority ethnic backgrounds tend to have lower value savings than White people. The median value of savings held by Black people is the lowest of the five groups we are able to analyse, at £2,000. Figure x: Median value of savings and investment by ethnic background (2007/08) White Indian Pak/Ban Other Black 0 500 1000 1500 2000 2500 3000 3500 Median value of savings & investments Source: Authors' calculations using FRS 2007/08 data Notes: Sample sizes: White = 8,504; Indian = 127; Pakistani/Bangladeshi = 41; Black = 108; Other = 168. Results for Pakistani/Bangladeshi adults should be treated with caution due to small sample size. Differences in account ownership and value between different ethnic groups are very likely to reflect, at least partially, differences in income. Official statistics shows that 52 per cent of people from a Pakistani or Bangladeshi background are living in poverty, compared to 17 per cent of White people (Department for Work and Pensions 2009a). Black people and individuals 36 from an Indian background also have a higher risk of income poverty than the White population (25 and 22 per cent respectively). FRS data only captures savings and investments held by regulated financial institutions. There is some evidence that some ethnic minority communities commonly use informal savings clubs or are more likely to have informal savings at home (Collard and Kempson 2005; Khan 2008). The new Wealth and Assets Survey (WAS) collects data on 'informal assets', such as cash held at home or lent to family or friends, although it only records savings worth £250 or more (see annex x for more details). Westaway and McKay (2007) also note that some ethnic minority groups, particularly people from Asian backgrounds, are more likely to have non-cash assets like jewellery, which they may use in a similar way to cash savings or investments. Again, the value of these kinds of assets is not collected in FRS data but is available in the WAS datasets. Pensions Figure x shows the differences private pension provision between men and women from the major ethnic groups in 2004/05. In each major ethnic group, both men and women are significantly less likely than their White counterparts to have a private pension. Just over 45 per cent of White males had a private pension in 2004/05 compared to just under a quarter of Black men and a fifth of Asian men. These appear to be very substantial inequalities and it is clear that a significant majority of ethnic minority adults are not building up private pensions to supplement their retirement incomes. Figure x: Proportion of men and women with a private pension by ethnicity, 2004/05 50 45 Men Women 40 % of adults 35 30 25 20 15 10 5 0 White Black Asian Mixed Source: Westaway and McKay (2007) Notes: Based on data from the Family Resources Survey 2004/05 37 Figure x also shows that in three of the major ethnic groups, women are less likely to have a private pension and the gender gap is similar among White, Asian and Mixed ethnic groups. However, Black women are more likely to have a private pension than Black men. Black women have a higher employment rate than Asian women, at around 60 per cent compared to 50 per cent for Asian women. But Black women's employment rate is five percentage points lower than that of men. However, Black women are more likely to work in the public sector which may in part explain their better private pension position. Drawing on FRS data from 2005/06, Steventon and Sanchez (2008) found that overall 53 per cent of White employees were accruing a private pension compared to 39 per cent of ethnic minorities. In each age group, White people are more likely to be accruing a private pension – except in the 60-64 age group, where 54 per cent of ethnic minority employees are accruing, compared to 46 per cent of White workers. There are many drivers of lower private pension provision among people from an ethnic minority background, including: lower employment rates, particularly among people of Pakistani, Bangladeshi and Chinese origin and among some ethnic minority women; higher rates of long-term unemployment and inactivity, part-time working and self-employment among some minorities, especially Pakistani and Bangladeshi people; lower earnings; a concentration of some ethnic minorities in sectors which have low private pension provision; and the younger age profile of some minority groups (Runnymede Trust 2007; Khan 2008; Steventon and Sanchez 2008). It is important to note that these patterns affect different ethnic minorities in different ways. For example, self-employed people do not have access to occupational pensions provided by employers and so cannot benefit from contributions made by employers on their behalf. They will not be eligible for the planned auto-enrolment into a qualifying workplace pension arrangement which comes into effect in October 2012, and which will require a minimum 3 per cent employer contribution to a defined contribution pension scheme or membership of a defined benefit scheme. Two thirds of self-employed people currently lack a private pension, and people from Pakistani, Bangladeshi, Chinese and non-British White backgrounds have an above-average likelihood of being self-employed (Runnymede Trust 2007). Steventon and Sanchez (2008) look at how the reforms in the 2007 Pensions Act may affect people from an ethnic minority background. They applied the reforms in the Act to FRS data from 2005/06 and found that, if the reforms had been in place in 2005/06, 15 per cent of White people would not have been entitled to the full BSP compared to 26 per cent of ethnic minorities. They also found that 24 per cent of White people would have had no entitlement to the State Second Pension compared to 35 per cent of non- White people. Insurance 38 FRS data shows considerable differences in the likelihood of adults from different ethnic backgrounds living in households with no insurance. Figure x shows that households headed by a White adult are more likely to have home contents insurance than households headed by all other broad ethnic groups. Households headed by Pakistani or Bangladeshi adults and by non- Caribbean Black adults are particularly unlikely to have home contents insurance, at 45 and 34 per cent respectively. In comparison, 81 per cent of White-headed households have home contents insurance. Figure x: Proportion of households with home contents insurance by ethnicity of head of household, 2005/06 – 2007/08 White Ethnicity of head of household Mixed Indian Pakistani / Bangladeshi Black Caribbean Other Black Other 0 20 40 60 80 100 % of households with home contents insurance Source: Department for Work and Pensions (2009b) Notes: Data from 2005/06, 2006/07 and 2007/08 has been combined to produce larger sample sizes. Sample sizes: White = 73,447; Mixed = 511; Indian = 1,055; Pakistani/Bangladeshi = 848; Black Caribbean = 771; Other Black = 808; Other = 981. Figure x attempts to give some explanation as to why ethnic minority households are less likely to have home contents insurance than white people. It shows whether adults live in households who lack insurance because they cannot afford it, or because they do not want it. Figure x: Reasons for lack of household contents insurance by ethnicity, 2007/08 39 60 50 40 % of adults 30 20 10 0 White Indian Pak/Ban Black Other Would like HCI but cannot afford Does not want HCI Source: Authors' calculations using Family Resources Survey 2007/08 Notes: Figures do not compare directly with those in figure x since they relate to adults rather than households; and are for 2007/08 rather than 2005/06 – 2007/08. Black people and people from a Pakistani or Bangladeshi background are particularly likely to want insurance but be unable to afford it. Approximately two thirds of adults from each of these two broad ethnic groups who live in households without insurance would like insurance but cannot afford it. This is likely to be partially explained by the high levels of poverty among certain minority ethnic groups, although it is interesting that Black people and those from a Pakistani/Bangladeshi background have an almost identical pattern of insurance ownership but Pakistani/Bangladeshi people are twice as likely as Black people to be poor (Department for Work and Pensions 2010a). This may suggest that Black people face additional barriers to accessing insurance, such as higher premiums or issues linked to awareness and financial capability. Figures from the LCF suggest that affordability is a particular problem for Black people. Figure x shows that households headed by a Black person spend a greater proportion of total expenditure on home contents insurance than other ethnic groups. This is likely to be linked to the lower overall expenditure of Black headed-households. Another explanation might be that Black households are judged to be a higher risk, perhaps because they are more likely to experience a burglary. However, data from the British Crime Survey shows that households headed by someone from an Asian or mixed ethnic background have a higher risk of household property crime compared to households headed by a White or Black person (Jansson 2005). Further research would be needed to ascertain whether Black households are spending a greater proportion of total expenditure on insurance purely because they much lower overall expenditure, or because they are paying higher premiums. Figure x: Expenditure on home contents insurance by ethnic group, 2008 40 Ethnic origin of head of household White Asian Black Other 0.0 0.2 0.4 0.6 0.8 Expenditure on HCI as % of total household expenditure Source: Authors' calculations using Living Costs and Food Survey 2008. Note: Sample sizes: White = 7,916; Asian = 252; Black = 60; Other = 121. Excludes 418 respondents whose ethnicity was recorded as unknown. Figures for some ethnic groups should be treated with caution due to sample size. Figure x also shows that households headed by Asian people spend slightly more of total expenditure on insurance than White families, despite their higher overall expenditure (see section 5), suggesting that Asian families may have higher insurance premiums. Again, further research into the premiums paid by people from different ethnic backgrounds would be needed to verify this. Affordable credit It is very difficult to identify research which specifically addresses the demand for affordable credit or problems with high-cost lending among ethnic minority communities. Khan (2010) suggests that people from some minority ethnic backgrounds have greater access to informal credit channels, including the use of 'kommitis' among some Pakistani communities, where resources are pooled and shared out. Khan also suggests that Black people in the UK are more likely to use credit unions. However, no data is provided to support these claims. Access to informal or alternative low-cost credit may help some communities to avoid high cost loans; however, some channels, including 'kommitis', are unregulated and may leave users vulnerable if problems emerge. Analysis of Ipsos Mori survey data on financial services commissioned by the Runnymede Trust found that people from every major ethnic group were more likely than British White people to take on credit11 (Khan 2010). The apparent willingness to take on credit was strongest among people from Pakistani and Chinese backgrounds. However, this finding may reflect need as well as willingness: individuals from some ethnic minority backgrounds may have a greater need for credit because of low income, rather than being inherently 11 Respondents were asked to rate their agreement with the following statement on a scale of 1 to 5: If I want something I will often buy it on credit and think about how I will repay the money later. No sample size is provided in the published report. 41 more open to using credit. Current data does not allow us to come to a concrete judgement on this. Financial advice A recent report by Mawhinney (2010) looks at the access of financial information by BME groups. It is based on the findings of 35 semi-structured interviews conducted through the summer of 2009 with people in three BME groups (Bangladeshi people in London, Chinese people in the North West, Black Caribbean people in the East of England) and 11 financial advice practitioners. The report highlights a number of issues relating to the access of financial information by these groups. It highlights what particular types of information BME groups normally need to access. As there are higher rates of unemployment and low economic activity in some BME groups compared to the White British population, there is often a greater need for advice around benefits. Other common concerns tend to be associated with poor working conditions, such as poor pay, a lack of National Insurance contributions, tax payments and prospects for pensions. The research found that some BME groups tend to have a lack of understanding about the way in which credit works, a problem that is often exacerbated by poor English language skills. The report highlights a distinction between BME people who are involuntarily excluded from accessing financial advice (for example those people who do not have access to bank accounts are unable to access advice from banks); and those who are voluntarily excluded (for example people who make a choice not to access different types of advice). Disability Transactional accounts Adults who report a DDA-defined disability are more than twice as likely to be 'unbanked' as those who do not. Figure x shows that 7 per cent of DDA- disabled adults lack an account compared to 3 per cent of non-disabled adults. This means that almost half of adults who are 'unbanked' (902,000 people) have a disability. Data from the FRS 2007/08 shows that approximately 13.4 million adults had a DDA defined disability, equivalent to 29 per cent of the adult population. Disabled adults are also twice as likely to have a saving or investment product but to lack a transactional account – a further 442,000 adults. Further analysis of disability and gender has found no significant differences in the risk of being 'unbanked' between disabled men and women, although women with a disability are slightly more likely to lack a transactional account but possess other savings or investments (full details in annex 2). Figure x: Account ownership by disability, 2007/08 42 100 No disability 80 DDA disabled % of adults 60 40 20 0 Unbanked No transactional Banked account Source: Authors' calculations using Family Resources Survey 2007/08 Note: Unweighted sample size: DDA disability = 13,414; no DDA disability = 30,014. Figures exclude 1,586 respondents whose account status was recorded as unknown. However, regression analysis using FRS 2006/07 data found that people with a long-standing illness or disability were slightly more likely to have a bank account than able-bodied adults once other factors had been taken into account (Finney and Kempson 2009). The same analysis found that people who were not working because of a permanent health condition or disability were four times as likely to lack a bank account. The pattern of account ownership shows a different trend over the lifecycle between disabled and non-disabled adults. Figure x shows a roughly u- shaped trend for the risk of being 'unbanked' among adults with no disability over the age of 25, with non-disabled people aged 60 to 64 being the age group who are least likely age group to have no account and the risk being higher for older age groups. The pattern for disabled people is very different, with a steady decline as people get older (after the age of 25), although the risk of being unbanked remains much higher for disabled people across every age group. Figure x: Risk of being 'unbanked' for different age groups, by disability status (2007/08) 43 12 10 Non-disabled Disabled 8 % of adults 6 4 2 0 4 4 4 4 9 4 4 4 -2 -3 -4 -5 -5 -6 -7 -8 16 25 35 45 55 60 65 75 Source: Authors' calculations using Family Resources Survey 2007/08 Notes: Differences between disabled and non-disabled adults with age groups are significant at the 5% level for each age group. Sample sizes are as above. FRS data allows us to look in some detail at account ownership among people with different kinds of disabilities or difficulties. FRS respondents are able to report a 'difficulty', such as difficulty with memory or with lifting and carrying, which would not necessarily qualify as a disability under the Disability Discrimination Act (but might do). Figure x is based on self-identified disability or difficulty so may exclude some respondents who have a DDA recognised disability but did not report a particular difficulty in any area of their life. Figure x shows the proportion of adults reporting different kinds of disabilities or difficulties who are unbanked or lack a transactional account. Figure x suggests that people with a learning disability or difficulty have the greatest risk of being unbanked among people with disabilities or difficulties, with 11 per cent of people reporting this kind of difficulty having no account. Adults with a communication disability (which includes those who are blind, partially- sighted, deaf or have speech difficulties) are least likely among disabled people to lack an account, although their risk of being unbanked remains higher than able-bodied adults. Figure x: Account ownership by type of disability/difficulty, 2007/08 44 12 10 Unbanked No trans a/c 8 % of adults 6 4 2 0 y er l ng ica n ilit th tio ni ob ys O ica ar M ph Le un er m th om O C Source: Authors' calculations using Family Resources Survey 2007/08 Notes: Individuals can report more than one kind of disability. Figures are for DDA disabilities and non-DDA difficulties so are not directly comparable to those presented in figure x. Sample size is over 1,000 for each type of disability/difficulty. We were also able to look at whether disabled people who are 'unbanked' are more or less likely than able-bodied people to live with other adults who have a bank account. However, we found no difference – 11 per cent of unbanked disabled people lived with no one who had a bank account, as did 11 per cent of able-bodied people. Several studies have found that disabled people may also face difficulties using some of the facilities associated with bank accounts, which may reduce the benefits of account ownership: A study which arranged for 750 physically disabled volunteers to survey the accessibility of 191 ATMs in 2006 found that 42 per cent of volunteers needed assistance to use the cash machine, and of the ATMs surveyed, 59 per cent were felt by disabled people not to be fully accessible. A quarter of all cash machines surveyed were found to have no Braille on the key pads, and 28 per cent were found not to be at a height that was accessible for a wheelchair user (Leonard Cheshire 2007). A survey of 1,000 adults with a disability found that over half of respondents (54 per cent) with a physical disability had sometimes found Chip and PIN keypads difficult to use, compared to 38 per cent of non-disabled respondents (Leonard Cheshire 2007). The survey also found that over a third (37 per cent) of disabled respondents who did not use Chip and PIN were not aware of the alternatives; only 20 per cent of disabled respondents who did not use Chip and PIN felt that retail staff were aware of alternatives. An RNIB and Citizens Advice telephone survey of 163 blind and partially sighted people found that ATMs were used by less than half (44 per cent) of respondents who had a bank account (RNIB 2004). 45 More than half of those respondents who did use ATMs found them either 'very' or 'somewhat' difficult to use. Savings and investments Figure x shows the proportion of adults who lack formal savings, for disabled and able-bodied adults and for people with different kinds of disability and difficulties. People with a disability or difficulty are slightly less likely to have savings compared to people who report no disability or difficulty, although the difference is not as large as with current account ownership. Figure x also shows that people who report difficulties with communication are more likely to have savings than people who report no disability or difficulty. However, half of people with a learning difficulty or disability lack savings, as do nearly 40 per cent of people with mobility problems. Our analysis has found no significant differences in the possession of savings between disabled men and women – 37 and 36 per cent lacked savings respectively. 60 50 40 % of adults 30 20 10 0 d ng er d n l y ca ie le t io ilit th ni od i ab ob ys ica O ar -b is ph M Le un ld le er Ab m Al th m O Co Total pop Type of disability Source: Authors' calculations using Family Resources Survey 2007/08 Notes: Individuals can report more than one kind of disability or difficulty. Figures are for DDA disabilities and non-DDA difficulties so are not directly comparable to those presented in figure x. Sample size: mobility difficulty = 6,436; communication difficulty = 1,724; other physical difficulty = 11,096; learning difficulty = 1,756; other difficulty = 9,288. Figure x shows the proportion of DDA disabled and able-bodied adults in each age group who lack formal savings. Two patterns stand out: the gap between disabled and able-bodied people aged 16 to 24 is quite narrow in terms of having savings; and the increase in lack of savings among older people affects able-bodied people but not disabled people. We previously found that this trend affected women but not men, so it seems that the small fall in possession of savings among older people is primarily experienced by able- bodied women. 46 70 60 Non-disabled 50 Disabled % of adults 40 30 20 10 0 4 4 4 4 9 4 4 4 -2 -3 -4 -5 -5 -6 -7 -8 16 25 35 45 55 60 65 75 Source: Authors' calculations using Family Resources Survey 2007/08 Note: Differences between disabled and non-disabled within each age group are significant at the 5% level. Analysis of FRS data also shows that the median value of savings held by people with a DDA-recognised disability is similar to that held by able-bodied adults, at £3,200 compared to £3,000. This is shown in figures x and x, which illustrate the distribution of the value of savings held by DDA disabled adults (figure x) and able-bodied adults (figure x). Figure x: Distribution of the value of savings and investments held by able- bodied adults, 2007/08 47 20 15 10 5 0 0 10000 20000 30000 40000 Value of savings and investments Source: Authors' calculations using Family Resources Survey 2007/08 Notes: Excludes adults with savings of zero or more than £50,000. Figure x: Distribution of the value of savings and investments held by DDA disabled adults, 2007/08 15 10 5 0 0 10000 20000 30000 40000 Value of savings and investments Source: Authors' calculations using Family Resources Survey 2007/08 Notes: Excludes adults with savings of zero or more than £50,000. 48 However, figure x shows that this is entirely caused by the higher value of savings held by disabled people aged 75 to 84 (nearly 70 per cent of this age group reports a DDA-recognised disability). For all other age groups, the median value of savings held by disabled people is similar than those held by able-bodied people. Based on this data, there is no evidence of financial exclusion among disabled people in terms of the value of savings. Figure x: Median value of savings by age and disability status, 2007/08 4500 Median value of savings and investments 4000 Able-bodied 3500 Disabled 3000 2500 2000 1500 1000 500 0 4 4 4 4 9 4 4 4 -2 -3 -4 -5 -5 -6 -7 -8 16 25 35 45 55 60 65 75 Source: Authors' calculations using Family Resources Survey 2007/08 Pensions Looking at the pension status of disabled people is not straightforward because of the dynamic nature (that is, the way in which people develop and or recover from a disability or experience changes in the nature or severity of a disability over their life-time) can change in nature or severity over the lifecourse) and age profile of disability. The labour market position of people with have a disability at some point in their working-age life will affect the pension entitlements of this group. On average, disabled people are much less likely to be in employment, more likely to be long-term unemployed or inactive, have lower average earnings if they do work, and be more likely to retire early (DWP/GEO/EHRC 2009; Steventon and Sanchez 2008). Disabled people also often have extra costs which are not fully covered by state benefits like Disability Living Allowance, and may therefore have less disposable income to put towards a pension than an able-bodied person with a comparable income. Analysis by Steventon and Sanchez (2008) found that a quarter of disabled people would have failed to build up entitlement to the Basic State Pension had the Pensions Act 2007 reforms been in place in 2005/06. This compares with 15 per cent of able-bodied people and suggests that disabled people may continue to face financial difficulties in retirement despite recent policy changes. Furthermore, a third of disabled people would not have had a 49 qualifying year for the State Second Pension, compared to a quarter of non- disabled people. However, Steventon and Sanchez (2008) also found no major difference between the proportion of disabled and non-disabled workers who were accruing a private pension provision. The key issue for working-age disabled people in terms of private pension provision is whether they are in work. Insurance According to FRS data, 77 per cent of adults who have a DDA-recognised disability live in households which have home contents insurance, compared to 83 per cent of able-bodied adults. Figure x also shows that 14 per cent of people with a disability live in households which would like insurance but cannot afford it, compared to 9 per cent of able-bodied adults. Figure x: Insurance status of households where disabled and able-bodied people live, 2007/08 90 80 No disability 70 60 DDA disabled % of adults 50 40 30 20 10 0 Yes Would like to but Doesn't want can't afford Does the household have contents insurance? Source: Authors' calculations using Family Resources Survey 2007/08 Notes: Sample size: Disabled adults = 13,414; non-disabled adults = 30,014. Figure x highlights the differences in insurance status among people with different types of disabilities. Almost a third of people with a learning disability or difficulty live in a household with no contents insurance. We have already seen that people with a learning disability or difficulty are more likely than other adults to be 'unbanked', and there may be legitimate reasons why some people with such disabilities cannot manage their own account. However, it is less obvious why there should be legitimate reasons for this group not having contents insurance. Figure x also suggests that the low take-up of insurance among this group is primarily the result of affordability problems rather than with awareness or financial capability that might be expected to result from their disability. Figure x: Insurance status of adults with different types of disability, 2007/08 50 35 30 Don't want 25 Want but can't afford % of adults 20 15 10 5 0 ng er n l y ca t io ilit th ni i ob ys ica O ar ph M Le un er m th m O Co Source: Authors' calculations using Family Resources Survey 2007/08 Notes: Unweighted sample size for each difficulty as above. The LCF does not collect information on disability so we are unable to provide data about the relative cost of insurance for disabled and able-bodied people, or to test the extent to which affordability is a particular problem for adults with a learning difficulty or disability. In other work, some concerns have been expressed about the internal processes within insurance companies which may overemphasise risk among people with mental health problems, and which may have staff members with insufficient knowledge of mental health issues (Office of the Deputy Prime Minister 2004). Affordable credit There is some limited evidence that people with disabilities are more likely to rely on alternative credit, which is likely to be high-cost, and may derive from illegal lenders: Research conducted for the National Consumer Council in 2004 found a high proportion of home credit customers had a limiting long-term illness or disability. Although this research was not statistically representative, the authors estimate that 45 per cent of respondents said they or their partner experienced a long-term illness or disability (Whyley and Brooker 2004)12. A study involving 51 physically disabled people and a survey of 400 members of Leonard Cheshire' supporters network found that both groups of respondents reported being seen as a 'higher risk' by their bank or building society. According to the report authors, this meant that respondents felt they had to pay substantially higher rates of interest on loans than non-disabled people, although no actual figures were given. Some respondents also reported that bank staff were unwilling to make adjustments to enable them to get access to services 12 Based on 109 interviews with low-income households in Leicestershire and Staffordshire in 2003. 51 and credit otherwise easily available to non-disabled people (Kober 2006). A nationally representative survey, comprising 8,580 respondents in Great Britain, found that 23 per cent of respondents with a mental health disorder13 were in debt compared to 8 per cent of respondents without a disorder14 (Jenkins et al, 2008). A survey of 725 adults in deprived neighbourhoods in Birmingham, Glasgow, Liverpool, London and Sheffield found that nearly one in three users of illegal lenders were in receipt of disability benefit and around a quarter were in receipt of incapacity benefits (Policis and Personal Finance Research Centre 2006). However, there is little evidence from large surveys or studies and further research may be required about the use of credit by disabled people. In particular, more research is needed to understand whether disabled people's use of high-cost credit is primarily driven by low income rather than disability. Financial advice Kober (2006) reports that 62 per cent of respondents in their research (outlined above) had sought advice from an independent advice service, most commonly from the local Citizens Advice Bureau. The key times for seeking advice tended to be either at the point where an individual's attempt to negotiate with a creditor had been unsuccessful, or when a creditor had commenced formal action. The majority of those who had sought advice had found it to be helpful. 13 Based on definitions contained in the World Health Organisation's International Classification of Diseases 1992 and measured in different ways depending on whether a disorder was judged to an alcohol or drug dependency, a common mental disorder or psychosis. 14 Debt was defined as being in arrears on a serious of household bills, including rent, mortgage repayments, utility bills and loan repayments. 52 Age Transactional accounts Figure x shows the risk of an individual being 'unbanked' or lacking a transactional account, for different age groups. Young adults (aged 16 to 24) clearly have the highest risk of being unbanked, at 6.3 per cent. After the age of 25, the risk of being unbanked then follows a rough u-shaped pattern, with the risk falling for people aged 35 to 64, but rising for older people. The proportion of people with some form of saving or investment but no transactional account follows a slightly different pattern, as it remains stable and low for people aged 16 to 59, but then rises significantly for older people, reaching over 5 per cent for adults aged 75 to 84. Older people are therefore more likely to have some form of saving or investment but to lack a transactional account that can be used for day-to-day financial transactions, as well as being slightly more likely to lack any kind of account. Figure x: Proportion of adults who are unbanked or lack a transaction account, by age (2007/08) 7 6 Unbanked 5 No transactional account % of adults 4 3 2 1 0 4 4 4 4 9 4 4 4 -2 -3 -4 -5 -5 -6 -7 -8 16 25 35 45 55 60 65 75 Source: Authors' calculations using Family Resources Survey 2007/08 Savings and investments As figure x shows, the age group which is most likely to lack formal savings are 16 to 24 year olds, 61 per cent of whom have no saving products. There is then a relatively sharp decline in the number of people who lack savings in each age group, until the 60-64 group. After the age of 60, the proportion of men who lack savings remains relatively stable, whereas it increases slightly among older women. This is the only real gender difference across the different age groups – up to the age of 55, men are very slightly less likely to have savings than women, but the difference is negligible. Figure x: Proportion of men and women with no formal savings, by age group (2007/08) 53 70 60 Male 50 Female % of adults 40 30 20 10 0 4 4 4 4 9 4 4 4 -2 -3 -4 -5 -5 -6 -7 -8 16 25 35 45 55 60 65 75 Source: Authors' calculations using Family Resources Survey 2007/08 As figure x shows, the average value of savings rises steadily for people between the age groups of 25-34 and 60-64, although it is higher for adults in the youngest age group. After the 60-64 age group, the average value of savings flattens out at £4,000 (except for men aged 65-74). These findings suggest that the majority of young people (age 16-24) have no formal savings but those who do have average savings which are comparable to those held by 45-54 year olds. Figure x: Median value of savings and investment by age and gender (2007/08) Median value of savings and investments 5000 Male 4000 Female 3000 2000 1000 0 4 4 4 4 9 4 4 4 -2 -3 -4 -5 -5 -6 -7 -8 16 25 35 45 55 60 65 75 Source: Authors' calculations using Family Resources Survey 2007/08 54 Insurance Figures x and x show the take-up of home contents insurance by age, for men and for women. Overall, take-up follows a similar pattern across the age groups for both men and women, with over half of males and females under 25 living in households with no contents insurance. This proportion then falls steeply so that just over 10 per cent of adults aged 60 to 64 live in households that lack insurance. Figure x shows that the proportion of men without contents insurance remains fairly stable for age groups after the 60 to 64 group. However, figure x shows a small increase in the proportion of older women who lack insurance after the age of 65. Figure x also shows that in the younger age groups, men are more likely to lack insurance because they cannot afford it. However, this pattern reverses in the oldest age group, with 65 per cent of women aged 75 to 84 lacking insurance because of affordability issues, compared to 32 per cent of their male counterparts. Figure x: Reasons for not having home contents insurance by age for males, 2007/08 60 Doesn't want 50 Would like but can't afford % of male adults 40 30 20 10 0 4 4 4 4 9 4 4 4 -2 -3 -4 -5 -5 -6 -7 -8 16 25 35 45 55 60 65 75 Source: Authors' calculations using FRS 2007/08 Figure x: Reasons for not having home contents insurance by age for females, 2007/08 55 60 Doesn't want 50 Would like but can't afford % of female adults 40 30 20 10 0 4 4 4 4 9 4 4 4 -2 -3 -4 -5 -5 -6 -7 -8 16 25 35 45 55 60 65 75 Source: Authors' calculations using FRS 2007/08 Pensions Membership and contributions to private pensions are closely associated with an individual's stage in life, and therefore with age. Figure x above highlights the different patterns in private pension membership across the age groups, with take-up of private pensions relatively low among people under 30; a peak in membership among people in middle age; and a slight decline among people nearing State Pension Age. Affordable Credit Survey and qualitative evidence suggests there is some relationship between age and the use of credit. Older people tend to have more negative attitudes to borrowing and do not feel as comfortable about being in debt as younger groups (McKay, Kempson, Atkinson and Crame 2008). A Mori poll of 2,805 low-income individuals in 18 areas of the UK conducted for the Financial Inclusion Taskforce found that 54 per cent of over 65s were not using any form of credit, compared to 26 per cent of working-age adults (Financial Inclusion Taskforce 2007). It is not clear if differences in attitudes to borrowing among different age groups are the result of cohort or age effects. That is, whether the current cohort of older people are uncomfortable with borrowing because borrowing was not as common in the past; or whether the acceptability of borrowing declines with age independently of the cultural factors around borrowing, in which case we would expect to see that borrowing declines with age in future generations. Data from the British Household Panel Survey in 2005 shows a steep increase in the use of unsecured credit between the ages of approximately 18 and 22, to around 60 per cent of people within that age group, followed by a gradual decline to almost zero for people aged over 80 (McKay 2008). 56 Studies also indicate that people under retirement age are more likely to use alternative or high-cost sources of credit. A Mori poll, of 2,400 home credit users conducted in 2004 found that people between the ages of 21 and 55 were more likely to use home credit than older age groups, or those aged 16 to 20 (Whyley and Brooker 2004). People aged 21 to 34 were particularly likely to be home credit customers. This age group makes up just over a quarter of the general adult population, but half of people who had used home credit. Conversely, adults aged 65 or over made up just 11 per cent of home credit customers, but accounted for 20 per cent of the overall population. There also appears to be a greater demand for affordable credit among younger age groups, which is probably linked to the greater use of credit by people below retirement age generally and the fact that younger people have not had the chance to build up as much savings as older age groups so will more likely to rely on credit to smooth consumption than older people. The study for the FIT found that people aged between 18 and 44, and in particular those between 25 and 34, were significantly more likely to be willing but unable to use low cost credit than older age groups. In contrast, 38 per cent of those unwilling to use low cost loans were over 65, compared to 16 per cent of those who were unable to (Financial Inclusion Taskforce 2007). Financial advice Age Concern (2008) calculated that in 2008 there were 600,000 people over the age of 64 in acute need of financial advice. The volatility within the pension market and pension regulation were both given as particular issues upon which older people need advice (Harrop and Jopling 2009). A survey of 2,000 adults conducted in 2008 found that young people are more likely to rely on family and friends for financial advice than older people. Half of survey respondents aged 18 to 34 went to family and friends for financial advice compared to a quarter of adults aged 35 or over (Reform and Chartered Insurance Institute 2008). The survey found that young adults prioritised trust, ability to explain clearly and ease of access as their priorities when accessing financial advice, rather than cost. 57 Religion or belief There are very few sources of data on inequalities in access to financial services and products among people from different religious groups. Most studies have focused on the potential exclusion faced by Muslims, due to the specific teachings about interest which are a feature of Islam (Martin 2009). However, studies have also found that Sharia-compliant financial products are now fairly widely available in the UK. For example, Sharia-compliant bank accounts are relatively widely available throughout the UK. The Islamic Bank of Britain has branches in Manchester, London, Coventry, Birmingham and Leicester, and Sharia-compliant products are also available from high street banks HSBC and NatWest. There have been some negative media reports of Sharia-compliant accounts, suggesting they offer more favourable terms to Muslims than non-Muslims (see for example Martin 2009). The Finance Act 2007 clarified the tax framework around Sukuk (an Islamic finance certificate, similar to an investment bond), making them more widely available (Ainley, Mashayekhi, Hicks, Rahman and Ravalia 2007). Islamic insurance products (Takaful insurance) are also available to UK consumers through HSBC, the Islamic Bank of Britain and others. However, products provided by credit unions and many micro-lending organisations are not suitable for Muslims and so there is a risk that Muslims are excluded from some of the tools designed to tackle financial inclusion (Collard, Kempson and Whyley 2001). Informal savings clubs operating in some Muslims communities and discussed above may help these communities access affordable credit (Atkinson 2006). Sharia-compliant products can be more complex or uncommon than other products, and so it is important that Muslim consumers have sufficient understanding of the product, particularly as the range and nature of products has expanded rapidly in the last few years. There are some potential problems with the regulation of Sharia-compliant products, as the Financial Services Authority cannot give guidance on Sharia principles, but rather can only regulate the explanation of products and associated risks. 58 Sexual orientation There has been very little research into the relationship between sexual orientation and financial exclusion. In general terms, Stonewall has found that lesbian, gay and bisexual (LGB) people are often perceived to be affluent and financially aware, which creates an assumption that financial exclusion is not a problem among LGB people. Stonewall points out that in fact incomes and standards of living vary significantly among LGB people and such assumptions can hamper efforts to improve financial inclusion among this equality group (Stonewall 2009). Direct communications with Stonewall failed to unearth any specific evidence about financial inclusion among LGB people. The extent of direct discrimination by financial service providers against LGB people is difficult to ascertain. A small-scale study by Williams and Robertson (2007), based on a survey of 403 LGB living in Wales, found that 4 per cent felt they had been discriminated against by their bank, 3 per cent by their mortgage provider, and 6 per cent by their life insurance provider. These numbers appear to be relatively small. However, it should be noted that the survey was not representative and the results could not be compared to the experiences of other people, including heterosexual people, who may feel discriminated against for other reasons. 59 Transgender status Evidence of inequalities in financial exclusion among transgender people is also very difficult to identify. A small number of studies have looked at discrimination experience by transgender people. Drawing on an online survey of 873 self-identified transgender respondents during August 2006, and qualitative data drawn from around 80,000 emails and online postings to transgender campaign groups, Whittle, Turner and Al-Alami (2007) found that 6 per cent of respondents said that they had experienced discrimination from banks. The major problem for transgender people relating to bank accounts was the failure on the part of banks to change their details promptly. The same study found that 7 per cent of research participants had experienced discrimination in dealing with their pension arrangements; and 7 had felt discriminated against when dealing with insurance companies. However, as already stated, it is difficult to compare this to the experiences of the overall population and to understand if transgender people face substantially more discrimination when dealing with the financial services industry then the general population. A separate survey of 499 self-identified transgender people in Lambeth in 2006 found that transgender people were more likely to have a problem with debt or paying bills (54 per cent) than others (32 per cent) and among people experiencing debt, trans-sexual people were much more likely to think their sexual identity or sexuality to be relevant (46 per cent) than were others (5 per cent) (Keogh, Reed and Weatherburn 2006). 60 4. Measures of access to affordable utilities We now turn to look at access to affordable essential services among the equality groups. These services include energy, water and telecommunications, and in this section we briefly outline the measures of access to essential services examined. Affordable energy Securing access to affordable energy services is a growing problem for households in the UK, largely because of rising energy prices. This has been driven since the late 1990s by rising oil and gas prices; and government policies designed to tackle climate change, which have tended to be levied on bills rather than be paid for out of government revenue (Bird, Campbell and Lawton 2010). These trends are expected to continue over the next decade at least. Major investment in energy infrastructure is also needed to maintain energy supplies and this is expected to push up energy bills further. Rising energy prices have led to an increase in fuel poverty in the UK since 2004, before which it had been on a downward trajectory. A household is defined as fuel poor if it would have to spend more than 10 per cent of its income on fuel in order to maintain an adequate level of warmth (Department for Energy and Climate Change 2009). Between 2004 and 2007 the number of fuel poor households in the UK doubled, rising from 2 million to 4 million (Department for Energy and Climate Change 2009). This represents approximately 16 per cent of all households in the UK, of which over 80 per cent (3.25 million) were classed as vulnerable. The UK Government, together with the devolved administrations, has a commitment to end fuel poverty by 2016 in England, Scotland and Northern Ireland and by 2018 in Wales. There is also a commitment to end fuel poverty in vulnerable households (those containing children or people who are elderly, ill or disabled) by 2010. This target has almost certainly been missed given the upward trend in fuel poverty and the expected continuing rises in energy prices. There are well-documented problems with the affordability of energy services for households who rely on pre-payment meters (PPMs), which tend to be associated with higher tariffs. Low-income households are more likely to use PPMs, often because they enable weekly budgeting of energy costs with no possibility of going in arrears. However, there is now very little difference between tariffs available on PPMs and those on Standard Credit (where bills are paid in arrears, usually quarterly), with the best tariffs available to Direct Debit customers, particularly those with online Direct Debit accounts (Thomas 2008). Disconnections are relatively rare, particularly for electricity, and have fallen significantly since the late 1990s. There is some evidence that gas disconnections are rising again, most likely because of rising energy prices (Thomas 2008). The Department for Energy and Climate Change (DECC) produces an annual fuel poverty statistics report with statistics for England and the UK, drawing 61 primarily on data from the English Housing Condition Survey (EHCS) (which became the English Housing Survey in April 2008). The devolved administrations also produce their own reports on fuel poverty statistics, drawing on similar survey data. The DECC report provides some demographic breakdown of fuel poverty figures; however, it only covers age among the equality groups. Communities and Local Government publish detailed standard tables from the EHCS which include data on the energy efficiency of homes broken down by certain characteristics of the head of household. We reproduce those tables in this report where relevant. Further analysis of EHCS data could provide useful data on the extent of fuel poverty among some of the equality groups; however, the data was not available to the authors at the time of writing this report. We have also carried out some limited original analysis of the Living Costs and Food Survey (LCF) 2008 to estimate spending on energy as a proportion of total household expenditure. Using the LCF, we are able to produce estimates of average household energy spending by age, ethnic origin and gender of the head of household. The data limitations of the LCF have already been noted (see page x). Affordable water services Water poverty is a much less prominent issue in the UK than fuel poverty. However, some households are facing rising water charges due to the changing climate and population pressures. Households are said to be experiencing water poverty if they are spending more than 3 per cent of their income for water services. High and rising water charges are a particular problem in south-west England because of the rural population and water scarcity, and similar problems could spread to other parts of southern England as the effects of climate change increase (Lobina and Hall 2008). Around a third of households have a water meter, and this figure is rising each year. Non-metered households are charged based on property values rather than actual usage so there is effectively a cross-subsidy between high and low volume users. This subsidy cannot exist among metered households and as the proportion of metered households increase, there are concerns about what this might mean for the affordability of water services for households which remain unmetered because they have high water consumption needs. This is likely to include larger families and households containing people with certain health conditions. There is very little up-to-date published data on water costs among the equality groups. We have carried out analysis of average household expenditure on water services as a proportion of total household expenditure, by age, gender and ethnicity of the head of household, using data from the LCF 2008. Affordable telecommunications 62 Telecommunications can be considered to be essential services because they enable people to maintain social contact, carry out many day-to-day activities and seek help in an emergency. Access to telephone and Internet services is becoming increasingly important as many products and services become accessible only, or primarily, by telephone or online. This applies to some financial services, creating a link between affordable telecommunications and financial inclusion. Many government services are also increasingly accessed through phone or Internet. Telephone and Internet services also often offer the lowest cost options, such as the lowest energy tariffs or the best interest rates. Unlike energy and water services, the cost of telecommunications has been falling in recent years. This is primarily because the telecoms market is large and has low entry costs, with a growing number of providers, products and services. However, this has also created additional complexity, which can be difficult for customers to navigate. This can be particularly problematic for people with poor numeracy and literacy skills, or particular disabilities. Household expenditure The following section of this report provides data on expenditure on energy, water and telephone charges. We present expenditure as a proportion of total household expenditure, rather than in cash terms, to take account of differences in family size and possible regional differences in charges and expenditure. However, this means that our expenditure figures are determined in part by differences in expenditure among different households. Table x sets out median weekly household expenditure for different types of families. Table x: Median weekly expenditure by head of household, 2008 Median weekly total Unweighted sample household expenditure All households £382 5,832 Gender of HRP Male £433 3,666 Female £300 2,166 Ethnicity of HRP White £383 5,193 Asian £407 168 Black £307 96 Other £371 116 Age of HRP 16 – 24 £355 130 25 – 34 £452 716 35 – 44 £505 1,160 45 – 54 £498 1,167 55 – 64 £395 1,047 65 – 74 £274 819 75 + £169 778 Source: Authors' calculations using Living Costs and Food Survey 2008 63 Table x shows significant differences in household expenditure between households headed by members of the different equality groups. Female- headed households have much lower household expenditure than those headed by men, which is likely to be because they are older on average; more likely to be single-adult households; and may also have lower incomes. Household expenditure appears to be much higher in households with an Asian head and much lower in households headed by a Black person. Given the sample size of the LCF it is not possible to look at more detailed ethnic backgrounds, which may help to explain some of these differences. Further research could be undertaken by joining a number of years' datasets together to boost sample sizes. Our measure of expenditure makes it difficult to ascertain if certain households are spending a greater proportion of their total expenditure on utilities because their overall expenditure is lower; or because they are more likely to be on higher tariffs. LCF data does not allow us to test this and we have not found any other research on this. Further research may be needed to ascertain whether households headed by members of certain equality groups are more likely to be on higher tariffs, which may be a result of a reduced choice of tariffs, less awareness about the costs and availability of different tariffs, different patterns of usage or possibly discrimination. 64 5. Access to affordable utilities among the equality groups Access to essential domestic services has received much less policy attention that financial inclusion over the last decade, and so there is much less data and other evidence to draw on. The exception is fuel poverty and the relationship with affordable energy services; however, as already noted, the focus in fuel poverty debates has been on older people, and the result is that there is a lack of data about the extent of fuel poverty among other equality groups. We have been unable to identify any evidence relating to the specific experiences of people of different religions, sexuality or transgender status in accessing affordable utilities. Gender Affordable energy Data from the Living Costs and Food Survey (LCF) 2008 show that households with a female head spend 5 per cent of total household expenditure on energy costs, compared to 4 per cent among male-headed households. This will partially reflect lower median household expenditure among households headed by women compared to male-headed households. Affordable water services Our analysis of LCF data has also found that female-headed households spend a greater proportion of their total expenditure on water charges – 1.8 per cent compared to 1.4 per cent for households with a male head. Again, this is in part due to the lower overall expenditure of households headed by women. Affordable telecommunications Almost all households have access to a telephone, whether fixed line or mobile and there are no major differences between male and female headed households, as table x shows. Data from Ofcom's consumer tracking survey shows no gender differences in mobile phone ownership, with around 90 per cent of both men and women using a mobile phone in 2009 (Ofcom 2009). Table x: Telephone services within households by gender of HRP, 2008 Proportion of households Fixed line and HRP Fixed line only Mobile only No telephone mobile Male 18 8 73 1 Female 25 10 64 1 All adults 21 9 70 1 Source: Authors' calculations using Living Costs and Food Survey 2008 Figure x shows that female-headed households spend a slightly greater proportion of overall expenditure on fixed-line calls, but there is no real 65 difference in spending on mobile phone charges between households headed by men and women. Table x: Household expenditure on telephone services as a proportion of total household expenditure by gender of HRP, 2008 Unweighted Unweighted HRP Fixed line Mobile sample sample Male 1.3 3,286 1.6 2,400 Female 1.8 1,855 1.7 713 All adults 1.5 5,141 1.6 3,113 Source: Authors' calculations using Living Costs and Food Survey 2008 Notes: Excludes expenditure on handsets. 66 Ethnicity Affordable energy Table x shows no major differences in household spending on energy costs among households of different ethnic backgrounds. Households headed by people with an Asian background spend a slightly greater proportion of total expenditure on energy costs, which is interesting given that these households had the greatest overall expenditure. Table x: Median household expenditure on energy as a proportion of total household expenditure by ethnic origin of HRP, 2008 Median expenditure on energy Unweighted sample White 4.4 4,913 Asian 5.2 164 Black 4.7 84 Other 3.9 109 Source: Authors' calculations using Living Costs and Food Survey 2008 Notes: Excludes 512 respondents who did not give details of ethnic origin. Estimates should be treated with caution due to small cell sizes. One reason may be that Asian families are more likely than other families to live in energy inefficient homes, meaning they have to spend a greater proportion of household expenditure than other families to achieve a similar level of thermal comfort. Using published data from the English Home Condition Survey (EHCS), figure x shows that 12 per cent of Asian families living in England live in homes judged by the survey to be energy inefficient, compared to 9 per cent of White families. However, a greater proportion of families from 'other' ethnic backgrounds (14 per cent) live in energy inefficient homes, so the relationship between energy expenditure and energy efficiencies of homes is not clear. Figure x: Proportion of households in England living in energy inefficient homes by ethnic origin of head of household, 2007 67 Ethnic origin of head of household White Black Asian Other 0 5 10 15 % of households Source: Communities and Local Government (2010) Affordable water services Our analysis of water charges using data from the LCF found that White households and those with an Asian or 'Other' ethnic background are spending a similar proportion of household expenditure on water services, at around 1.5 per cent. However, Black families were spending 2 per cent of household expenditure on water services. This will partly reflect lower overall expenditure among Black families and is perhaps not a large enough difference to draw any conclusions. Affordable telecommunications Data from Ofcom's consumer tracking survey and our own analysis of LCF data suggests there is little difference in access to affordable telecoms services among different ethnic groups, and therefore there are no particular equality concerns when it comes to this measure. Ofcom's consumer tracking survey also suggests that there are few differences in the take-up of telephone services between White and non- White consumers, although the relatively small sample size makes it difficult to draw conclusions about particular ethnic groups (Ofcom 2009). Figure x shows no major differences in spending on telecoms services among ethnic groups Figure x: Household expenditure on fixed line and mobile services as a proportion of household expenditure by ethnicity of HRP, 2008 68 2.5 % of household expenditure 2.0 1.5 1.0 0.5 0.0 White Asian Black Other Fixed line Mobile Source: Authors' calculations using Living Costs and Food Survey 2008 Ofcom's tracking survey shows that 77 per cent non-White households have internet access compared to 66 per cent of White households, although Ofcom cautions against overinterpreting this figure due to small sample sizes (Ofcom 2009). 69 Age Affordable energy Figure x shows that households expenditure on energy increases with age (excluding households headed by women aged 16 to 24). Overall, households headed by someone aged 75 or over spend an average 8.2 per cent of total expenditure on energy, compared to 3.7 among households headed by 16 to 24 year olds. This is partly because households with older HRPs have much lower average expenditure than working-age households. This may also explain the widening gap between households headed by men and women. Figure x: Household energy expenditure as a proportion of income by age and gender, 2008 12 Household expenditure on energy as % of 10 Male 8 total expenditure Female 6 4 2 0 + 4 4 4 4 4 4 -2 -3 -4 -5 -6 -7 75 16 25 35 45 55 65 Age of head of household Source: Authors' calculations using Living Costs and Food Survey 2008 Notes: Actual expenditure is not an accurate measure of fuel poverty, as fuel poverty is based on the proportion of income that would have to be spent to keep a home at a minimum level of warmth, not actual energy expenditure. However, figure x shows that adults aged over 85 also have a particularly high risk of living in a home with poor energy efficiency. This will add to fuel bills and increase their risk of experiencing fuel poverty. Figure x also shows, however, that households whose oldest resident is aged 16 to 24 have the highest risk of living in an energy inefficient home, despite our findings that younger heads of households spend the lowest proportion of total expenditure on energy. This may be because such households spend less time at home or require a lower degree of thermal comfort. Figure x: Proportion of English households living in energy inefficient homes by age of oldest resident, 2007 70 14 12 % of households 10 8 6 4 2 0 + 4 4 9 9 4 4 -2 -3 -4 -5 -7 -8 85 16 25 35 50 60 75 Age of oldest resident Source: Communities and Local Government (2010) However, figure x also shows that households whose oldest resident is aged 16 to 24 have a very similar risk of fuel poverty as those where the oldest resident is 85 or over. Over a quarter of households in England where the oldest adult is aged under 25 or over 84 are living in fuel poverty. Patterns of energy efficiency and fuel poverty by age are not identical because living in an energy inefficient home is not the only driver of fuel poverty. Figures x and x also show that expenditure on energy is not always a good proxy for fuel poverty, and further analysis of the experiences of fuel poverty among the equality groups may be useful. Figure x: Proportion of English households experiencing fuel poverty by age of oldest member of household, 2007 30 25 % of households 20 15 10 5 0 4 4 9 9 4 4 + -2 -3 -4 -5 -7 -8 85 16 25 35 50 60 75 Age of oldest member of household Source: Department for Energy and Climate Change (2009) Affordable water services 71 LCF data in figure x shows that expenditure on water services follows a very similar pattern to energy spending across the age groups, gradually increasing as a proportion of household expenditure and being higher for female-headed households. The particularly high water expenditure of households headed by women aged 75 or over means that our figures suggest that the average person in this group is experiencing water poverty. Figure x: Expenditure on water services as a proportion of household 3.5 Expenditure on water charges as % 3.0 Male of household expenditure 2.5 Female 2.0 1.5 1.0 0.5 0.0 + 4 4 4 4 4 4 75 -2 -3 -4 -5 -6 -7 16 25 35 45 55 65 Age of head of household Source: Authors's calculations using LCF 2008 Affordable telecommunications Findings from Ofcom's consumer tracking survey show opposing trends in access to fixed line and mobile telephones by age. Figure x shows that nearly 100 per cent of people aged 15 to 44 personally use a mobile telephone, compared to 71 per cent of 65 to 75 year olds, and just 54 per cent of people aged 75 or over. Conversely, take-up of fixed line telephone services is almost universal (between 95 and 97 per cent) among people aged 65 or over, whereas only 72 per cent of people aged 15 to 24 have a fixed line phone in their home. Figure x: Take-up of fixed line and mobile telephone services by age, Q2 2009 72 100 90 80 70 % of adults 60 50 40 30 20 10 0 15 - 24 25 - 44 45 - 64 65 - 74 75+ Fixed line Mobile Source: Ofcom (2009) Note: Mobile take-up is measured by individuals who personally use a mobile phone; fixed line take-up is measured by whether an individual has access to a fixed line in their home. It is not yet clear whether this differential access to fixed line and mobile phone services is detrimental for particular age groups. Data from both Ofcom and the LCF shows that the vast majority of households have access to some form of telephone communications, and it could be argued that the type of service used is a matter of personal choice. There is also likely to be a cohort effect at play so that in future years, people in older years will be increasingly likely to have mobile phones. Analysis of LCF data found that expenditure on fixed line and mobile calls followed the patterns of fixed line and mobile take- up among different age groups, with no major differences between men and women within age groups. Figure x shows trends in the take-up of home internet by age between 2005 and 2009, drawing on data from Ofcom's consumer research. Take-up is at very similar levels for each age group up to 64, at between 79 and 84 per cent. These age groups have also seen relatively significant increases in take- up, particularly between 2008 and 2009. However, take-up of internet is much lower among older age groups, at 41 per cent for the 65 to 74 group and just 22 per cent for people aged 75 and over. These older age groups have also seen slower growth in internet take-up in recent years: take-up has been relatively stagnant among the 65 to 74 age group for the last three years and only increased by three percentage points between 2008 and 2009 for people aged 75 or over. Again, it not clear whether the lower take-up of internet among older age groups is due to age or cohort effects, and how patterns of internet use among different age groups might change over time. Figure x: Take-up of home internet by age, 2005 - 2009 73 90 80 2005 2006 2007 70 % of respondents 2008 2009 60 50 40 30 20 10 0 15 - 24 25 - 44 45 - 64 65 - 74 75 + Source: Ofcom (2009) Ofcom research shows that the main driver for older people not having access to the internet is the lack of access to a home computer. Less than half (46 per cent) of people aged 65 to 74 and less than a third (28 per cent) of people aged 75 or over had a computer in their home in 2009 (Ofcom 2009). This compares with an average of 76 per cent across the whole population. A Mori survey conducted on behalf of Ofcom also found that 43 per cent of respondents without home internet said they had no plans to get internet access at home; that this group tended to be over 65; and that people who lacked internet access because of issues of affordability were more likely to be over 65. This suggests that many older people without internet are unlikely to take it up in the near future, some because of affordability problems. It is clear that many older people are not currently able to benefit from internet access, and this may continue for a number of years. Further research may be needed to understand what impact this is currently having on their quality of life and what the future impact may be as more services migrate to the internet, particularly if access to the internet does not increase among older age groups. 74 Disability The LCF does not collect data on disability status so we are not able to provide estimates of expenditure on utilities for households containing people with a disability or long-term health condition. There is limited evidence from other sources about disabled people's access to affordable utilities and telecommunications. Affordable energy There is a clear link between some kinds of disability and fuel poverty. People with some kinds of disability may spend more time at home or require a higher degree of thermal comfort because of their condition. Disabled people also live in lower income households on average and the overlap between disability and older age means that many older disabled people are likely to be experiencing fuel poverty. The current measure of fuel poverty may also underestimate fuel poverty among disabled people. This is because it is based on minimum standards of thermal comfort that may not be appropriate for people with some disabilities or health conditions; and like other income- based measures of poverty, does not take account of the extra costs of disability (Laxton and Parckar 2009). Despite the relationship between fuel poverty and disability, it can be difficult to establish robust figures for the number of disabled people experiencing fuel poverty. Laxton and Parckar (2009) point to government estimates from 2005 which suggest that 98,000 households in fuel poverty contained a disabled person under 60. However, fuel poverty has increased significantly since 2005 and this figure is likely to have increased as well. Laxton and Parckar (2009) suggest that many of the same factors which cause fuel poverty to be high among older people also apply to disabled people and so fuel poverty is likely to be high among disabled people; however, they are unable to provide any official statistics to support this. The EHCS should be a reliable source of data on fuel poverty among disabled people, at least in England. Data from the EHCS 2007 shows that households containing a disabled person are no more likely to be living in energy inefficient households than other households: 9 per cent of households containing someone with a disability are living in energy inefficient homes compared to 10 per cent of other households. However, this does not mean that there is no difference in the risk of fuel poverty between households with and without disabled members, since households contain disabled people have lower average incomes (Department for Work and Pensions 2010). Further analysis of EHCS data is required. Affordable telecommunications Ofcom's consumer research asks about disability status but the achieved sample of disabled consumers is relatively low (around 300 respondents). It also does not include all types of disability, collecting data only on visual, hearing and mobility disabilities. The age profile of disabled people is also likely to have an effect on the use of telecommunications services by disabled people. 75 Ofcom was able to conduct interviews with 69 visually impaired people, 100 hearing impaired people and 124 people with a mobility disability. There was no difference in the take-up of a fixed-line telephone between people with visual, hearing and mobility disabilities and people with no disability. Figure x shows that people with each of the three disabilities monitored by Ofcom are less likely personally to use a mobile phone; and are less likely to have internet access. Less than half of people with a visual, hearing or mobility disability have access to the internet at home. Ofcom also found some evidence that 'involuntary' non-ownership of home internet was higher among people with one of the three disabilities. The largest reason given for 'involuntary' non-ownership among the general population was problems with affordability. Figure x: Use of mobile and home internet among people with some types of disability, 2009 100 90 Mobile 80 % of respondents 70 Internet 60 50 40 30 20 10 0 All Visual Hearing Mobility respondents disability disability disability Source: Ofcom (2009) Notes: Mobile use relates to individuals who personally use a mobile phone; Internet relates to people who have access to Internet within their home. Sample size: visual disability = 69; hearing disability = 100; mobility disability = 124. The Ofcom consumer tracking survey also found that 59 per cent of respondents with a hearing disability had problems using communications services, as did 30 per cent of visually impaired people and 25 per cent of people with a mobility disability. Among all respondents, this figure was just 11 per cent. This may be a further explanation for why some disabled people are less likely to have a mobile or home internet access. 76 Qualitative research conducted by Ofcom with 40 telecoms consumers who had upper-body mobility or dexterity problems found that use of the internet was important for maintaining social contact and performing day-to-day tasks (Ofcom, 2009). However, the study also found that consumers often had difficulty installing telecoms equipment (this was more problematic than using equipment); and had limited awareness of adaptations available to telecoms equipment and services which could make them easier to use. 77 6. Conclusions The data presented in this report shows important differences in the way in which people with different characteristics are able to consume financial services. Some differences are to be expected – such as differences in saving rates across different age groups – and should not necessarily be the cause of great concern or policy attention. In some cases, there are no real variations between people from different equality groups – for example, in account ownership by men and women – and therefore no need for action. However, in some cases, there is evidence of inequality and exclusion that may need addressing; and sometimes there has been insufficient evidence to draw any conclusion. In this final section, we attempt to classify the inequalities we have identified into three broad groups, in order to pull all the data contained in this report into a coherent evidence base for further action. Areas where there is no evidence of inequality or exclusion Ownership of bank accounts, savings and home contents insurance by men and women Areas where differences could be justified Areas where there is insufficient evidence Areas where there could be real inequalities and exclusion requiring action Gender On some of the key measures of financial exclusion and access to affordable utilities, there were no real differences between the position of men and women. This would include ownership of a bank account, savings and home contents insurance and spending on utilities. In other areas, most notably pensions, women continue to experience important inequalities relative to men. This study has also found evidence that women are more likely than men to use high-cost credit and to be negatively affected by life transitions like divorce or parenthood. In all of the cases where women experience inequalities relative to men, there is evidence that this is at least in part a result of women's poorer average economic position compared to men, in terms of both income and employment. Boosting women's incomes and employment status may therefore help to address some of these inequalities. Ethnicity This study has found evidence of significant financial exclusion among some ethnic minority groups, particularly among Pakistani and Bangladeshi families. People from a Pakistani or Bangladeshi background appear to be much less likely than White people to have a bank account, formal savings, home 78 contents insurance or private pension provision. Generally, people from other ethnic backgrounds (including Black and Indian people) were less likely to have financial products compared to White people, but the differences were smaller than for Pakistani or Bangladeshi people. There was no evidence of major differences in spending on essential services among different ethnic groups, although some ethnic minority households were more likely to live in inefficient housing, which could lead to higher energy spending. As with women, the position of Pakistani and Bangladeshi people is likely to be influenced by their income and employment status, which tends to be the lowest on average among broad ethnic groups. Among other measures of financial exclusion, notably access to affordable credit and financial advice, there is very little evidence about how people from minority ethnic backgrounds fare relative White people, and this may require further research. Within minority ethnic groups, it can be difficult to look at differences between men and women because of small sample sizes in household surveys. The evidence we were able to collate suggests that women from Indian, Pakistani and Bangladeshi backgrounds are probably more likely to experience financial exclusion when it comes to bank accounts and private pensions. Disability There is also some important evidence of inequalities experienced by disabled people relative to able-bodied people. This was true for bank account ownership, contents insurance and pension provision, although not savings. On average, disabled people have lower incomes and are less likely to be in employment, and these factors will drive some of the financial exclusion experienced by this group. Further research may be needed to examine the use of affordable and high-cost credit among disabled people and the extent o which this is driven by low income. We did not find any differences in exclusion between disabled men and women. Among people with different disabilities or difficulties, adults with learning difficulties or disabilities were most likely to experience some forms of exclusion, notably ownership of bank accounts, savings and contents insurance. In some cases, it will not be appropriate for people with learning difficulties/disabilities to have control over their own finances, which could explain some of the exclusion. However, this is not always the case and more research may be needed to understand why people with learning difficulties/disabilities lack certain financial products. In particular, learning disabled people should be able to live in households that have home contents insurance, either because they live with people without a learning disability or because their insurance has been arranged by someone else. Age The major inequalities in financial services experienced by different age groups is the higher risk of some forms of financial exclusion among young adults. Young adults (primarily those aged 16 to 24) are less likely to have a 79 bank account, savings, pension provision and home contents insurance and appear to be more likely to use credit, including high-cost credit. In some cases, this is not problematic – for example, people aged 16 to 24 cannot be expected to have accumulated substantial savings or pension provision. In other cases, there may inequalities that need addressing. Although the low take-up of bank accounts among young adults is likely to be an age effect (i.e. they will open an account later in life) and a sizeable proportion can probably benefit from accounts owned by others in their household, the lack of an account could be problematic for some young people. Young men in particular are more likely to lack an account than young women. The large proportion of young people who live in households that lack home contents insurance is also of concern, although the contents of such households are arguably lower in value than average. The propensity of young people to use credit, including high-cost credit, could be a generational issue that is of concern, although it is unlikely to have equality implications if this is the case. Other equality groups Although we uncovered some qualitative studies of people's interactions with financial services among the sexuality, religion or belief and transgender equality groups, there were not sufficient to allow to draw any conclusions about inequalities experienced by these groups relative to the wider population. 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London: TUC Westaway J and McKay S (2007) Women's Financial Assets and Debts London: Fawcett Society Williams and Robertson (2007) Counted In: Stonewall Cymru survey of lesbian, gay, bisexual people in Wales 2006 Cardiff: Stonewall Cymru Whittle S, Turner L and Al-Alami M (2007) Engendered Penalties: Transgender and transsexual people's experiences of inequality and discrimination London: Equalities Review / Communities and Local Government Whyley C and Brooker S (2004) Home Credit: An investigation into the UK home credit market London: National Consumer Council 85 Annex 1: Major household surveys used in this report Family Resources Survey: an annual survey of approximately 25,000 UK households, providing detailed data on household income, savings and pensions. Living Costs and Food Survey: previously called the Expenditure and Food Survey, the LCF surveys approximately 6,000 households in the UK each year and provides data on household expenditure. General Lifestyle Survey: a survey of around 9,000 households in Great Britain, which contains detailed pensions data. British Household Panel Survey: a longitudinal survey that began in 1991 and has a sample of approximately 10,000 households from across the UK. Data collected includes income, expenditure, pensions, savings and debt. English House Conditions Survey: surveys around 16,000 households every two years and was merged into the English Housing Survey in 2008. The EHCS contains data on housing conditions, including energy efficiency and fuel poverty. Similar surveys operate in Wales, Scotland and Northern Ireland. Ofcom Residential Communications Tracking Survey: questions around 2,000 adults each quarter about their use of various telecommunications services. Headline findings are robust to 1 per cent significance. 86 Annex 2: Accounts identified in the Family Resources Survey Current accounts National Savings Bank ordinary accounts National Savings Bank investment accounts Savings and investments not listed elsewhere Government gilt-edged stock Unit and investment trusts Stocks, shares and bonds PEPs National Savings capital bonds Index-linked National Savings certificates Fixed-interest National Savings certificates Pensioners Guaranteed Bonds SAYE schemes Premium bonds National Savings income bonds National Savings deposit bonds First Option bonds Yearly Plans ISAs Profit-sharing schemes Company share option plans Share clubs Fixed-rate savings bonds Guaranteed Equity Bonds Basic Bank Accounts Credit Union accounts Endowment policies Post Office Card Accounts 87 Annex 3: Wealth and Assets Survey The Wealth and Assets Survey is a new survey of the household wealth in the UK. It is a longitudinal survey and the first wave was completed between July 2006 and July 2008; wave two fieldwork will take place between July 2008 and July 2010; and a third wave is planned for 2010-12 (Daffin 2009). The WAS collects detailed data on pensions, property, savings and investments, other assets, debt and attitudes to financial issues. The 2006/08 wave collected data on 30,595 private households. The full dataset for 2006/08 has been placed with the UK Data Archive; however, access requires Approved Researcher status under ONS rules and it was not possible to obtain in time to complete this report. This note sets out the future potential uses of the WAS for investigating financial inclusion among the equality groups. The WAS collects demographic data which allows the identification of five of the seven equality groups: Age Gender Ethnicity Religion: regardless of whether actively practising (Christian, Buddhist, Hindu, Jewish, Muslim, Sikh, Other, None); whether actively practising Disability: whether respondent has any long-standing illness, infirmity or disability; what kind of substantial difficulties: mobility; lifting/carrying; manual dexterity; continence; communication; memory; recognising when in physical danger; physical coordination; other Pension variables The WAS collects detailed data on all private pensions held by respondents, including those to which the respondent is no longer contributing: Membership Whether employer offers an occupational pension Whether respondent is eligible Whether respondent is a member If respondent is not a member, why not Contributions Whether employer makes contribution to a pension scheme on behalf of the respondent; and value of employer contributions Whether respondent is contributing to a private pension, and value of contributions Additional irregular contributions It not contributing, why not Type Pension type: occupational; group personal/stakeholder; private personal/stakeholder; other Number of years respondent has held pension for 88 Whether money purchase or salary-based Value / future income Expected income in retirement from private pensions Value of current pension fund Expected income from all pensions How respondents expect to fund retirement Savings and investments Type of account/investment: current account; savings or deposit account; ISA; fixed-term investment bonds; PEP; unit/investment trusts; employee shares; other shares; premium/NS bonds; bonds and gilts; life insurance; credit union; other; none Value of all savings account (in bands) and value of each type of account; current account balance Income from savings and investment in last 12 months Value of savings over £250 held in any of the following: given to someone else to look after; loaned to someone else; in a savings club; saved in cash at home Credit Credit and store cards Number of cards For each card, whether, on most recent statement, respondent repaid balance in full; repaid in part; not yet made a payment; no balance to pay Balance on most recent statement for each card Whether two or more payments behind on any card, and how much is owed in missed payments Alternative credit For each of separate mail order catalogue debt and goods bought on instalment from shops and suppliers: Number of credit agreements Whether interest is charged Amount of regular repayments/instalments Whether two or more instalments behind, and how much is owed in missed payments Loans Number of loans: personal loan from a bank; cash loan from home credit company; loan from pawnbroker; loan from credit union; loan from social fund; loan from employer, friend or relative; student loan; loan from payday lender; other Value of each loan Reason each loan was taken out: to spend on a particular item; to pay bills; refinance other borrowing; pay off other debts; make ends meet; other 89 Amount of regular loan instalments and payment periods Whether two or more repayments missed and value of missed payments All Whether all credit repayments are a heavy burden; somewhat of a burden; not a problem at all Financial advice Have you ever sought any help or advice because of debt, from: a free advice agency; a fee-charging debt advice company; an insolvency practitioner; accountant, bank manager, solicitor; friends or relatives; other. 90
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