Reflection - Learning Launch 

 Challenge 

 I am a part of the IT team ( 2 people ) in a newly created financial technology startup and the   given mandate from our shareholder is to provide an alternative financial product to large   segment of society whom other financial players do not serve . The team that is in charge of the   product , consists of Operation , Marketing , Finance and HR . Our main mission is to provide   financial product to those who “ need ” it , not only to those who “ want ” it . Apart from that , our   shareholder is also expecting a profitable business model from it , while at the same time we   have limited marketing budget and initial capital / fund to build the financial product itself . 

 Selection 

 Our team has already gone through several design thinking activities / tools , so we are ready to   try the learning launch tool . This learning launch exercise is small real life test where we can   justify our hypothesis of the new product to a small and segmented group of users with   expectation to cultivate the feedback fast thus we can learn faster from it . 

 Application 

 For our first learning launch , we focused on the financial product itself as well as the customers   segment . This tested our assumption that middle and low class of society whom Banks can not   afford to serve , they need an alternative   lending products which they can access easily and   fast . Our team went to several public markets at the city to directly meet with potential   customers , offer them the product and ask what their most painful experience , especially when   it comes to access to lending products , as well as for some of them , we asked how they fulfill   their needs on the lending itself . From those customer meetings , we learned that most of the   society in middle and low class , are not served by the Banks ( most of the Banks either reject   them or take a massive amount of time to assess their credit worthiness ) . Furthermore , we also   learned , they want to have faster and easier assessment process during the loan application   itself and interestingly , they do not care that much on interest rate , as long as they can afford   paying the installment . The main reason is currently they available loan provider for this   segment is Loan Sharks that charges a huge interest rate .     For our second learning launch , we focused on the channel distribution of the product . Our main   hypothesis , in this digital era , customers expect they can have access to their loan , not only   applying but also monitoring the process until the payment , from online presence , either mobile   app or website . We created a MVP ( minimum viable product ) for our website and mobile app ,   then launch it to market . We provided them some campaigns in Social Media and Search   Engine with a limited online marketing budget . From this second launch , we learned that market 

 acceptance of digital channel for distributing the lending product has a huge potential , especially   in mobile app . This supported by smartphone penetration and proved by number of downloads   we got within a short period of time with a limited budget . 

 Insight 

 By applying the learning launch tool , our team could easily identify our hypothesis and designed   launches to test these hypotheses . Additionally , we thought through anticipated results ,   expecting to find that an alternative lending product which is provided to middle and low class of   customers whom other Financial Institutions do not serve , is the product specification we will   focus on for our new business . Furthermore , digital channels provide an easy access to this   market segment . Our actual result was already inline from what we anticipated , however since   we have a limited budget , to have very effective launch , our focus will be on mobile app for our   channel , since it brought better number of customers . Moving forward , our team will move to   launch the product within limited cities and number of customers to serve . This limitation is set in   order to get more insights on the credit assessment model which needs to be fast , yet still cover   the risk of unpaid customers . 

 Approach 

 Given that our team has already gone through several design thinking activities / tools and are at   this stage , the learning launch is the appropriate tool . As previously mentioned , our team needs   to review the credit assessment process to have faster , yet safe to minimize risk of unpaid   customer during the upcoming launch . Future next launch , we are expecting to be closer to full   launch condition of the product itself . 


EMAIL: 
ID_NUM: 
NAME_STUDENT: 
PHONE_NUM: 
STREET_ADDRESS: 
URL_PERSONAL: 
USERNAME: 

### Task: You are a PII (Personal Identity Information) Detection. Given a essays written by students, you have to identify ONLY the following:
NAME_STUDENT - The full or partial name of a student that is not necessarily the author of the essay. This excludes instructors, authors, and other person names.
EMAIL - A student’s email address.
USERNAME - A student's username on any platform.
ID_NUM - A number or sequence of characters that could be used to identify a student, such as a student ID or a social security number.
PHONE_NUM - A phone number associated with a student.
URL_PERSONAL - A URL that might be used to identify a student.
STREET_ADDRESS - A full or partial street address that is associated with the student, such as their home address.
### Input: Reflection - Learning Launch 

 Challenge 

 I am a part of the IT team ( 2 people ) in a newly created financial technology startup and the   given mandate from our shareholder is to provide an alternative financial product to large   segment of society whom other financial players do not serve . The team that is in charge of the   product , consists of Operation , Marketing , Finance and HR . Our main mission is to provide   financial product to those who “ need ” it , not only to those who “ want ” it . Apart from that , our   shareholder is also expecting a profitable business model from it , while at the same time we   have limited marketing budget and initial capital / fund to build the financial product itself . 

 Selection 

 Our team has already gone through several design thinking activities / tools , so we are ready to   try the learning launch tool . This learning launch exercise is small real life test where we can   justify our hypothesis of the new product to a small and segmented group of users with   expectation to cultivate the feedback fast thus we can learn faster from it . 

 Application 

 For our first learning launch , we focused on the financial product itself as well as the customers   segment . This tested our assumption that middle and low class of society whom Banks can not   afford to serve , they need an alternative   lending products which they can access easily and   fast . Our team went to several public markets at the city to directly meet with potential   customers , offer them the product and ask what their most painful experience , especially when   it comes to access to lending products , as well as for some of them , we asked how they fulfill   their needs on the lending itself . From those customer meetings , we learned that most of the   society in middle and low class , are not served by the Banks ( most of the Banks either reject   them or take a massive amount of time to assess their credit worthiness ) . Furthermore , we also   learned , they want to have faster and easier assessment process during the loan application   itself and interestingly , they do not care that much on interest rate , as long as they can afford   paying the installment . The main reason is currently they available loan provider for this   segment is Loan Sharks that charges a huge interest rate .     For our second learning launch , we focused on the channel distribution of the product . Our main   hypothesis , in this digital era , customers expect they can have access to their loan , not only   applying but also monitoring the process until the payment , from online presence , either mobile   app or website . We created a MVP ( minimum viable product ) for our website and mobile app ,   then launch it to market . We provided them some campaigns in Social Media and Search   Engine with a limited online marketing budget . From this second launch , we learned that market 

 acceptance of digital channel for distributing the lending product has a huge potential , especially   in mobile app . This supported by smartphone penetration and proved by number of downloads   we got within a short period of time with a limited budget . 

 Insight 

 By applying the learning launch tool , our team could easily identify our hypothesis and designed   launches to test these hypotheses . Additionally , we thought through anticipated results ,   expecting to find that an alternative lending product which is provided to middle and low class of   customers whom other Financial Institutions do not serve , is the product specification we will   focus on for our new business . Furthermore , digital channels provide an easy access to this   market segment . Our actual result was already inline from what we anticipated , however since   we have a limited budget , to have very effective launch , our focus will be on mobile app for our   channel , since it brought better number of customers . Moving forward , our team will move to   launch the product within limited cities and number of customers to serve . This limitation is set in   order to get more insights on the credit assessment model which needs to be fast , yet still cover   the risk of unpaid customers . 

 Approach 

 Given that our team has already gone through several design thinking activities / tools and are at   this stage , the learning launch is the appropriate tool . As previously mentioned , our team needs   to review the credit assessment process to have faster , yet safe to minimize risk of unpaid   customer during the upcoming launch . Future next launch , we are expecting to be closer to full   launch condition of the product itself .
### Output: 