Using open-source and freely available data science tools, we took a historical book of catastrophe-exposed commercial property insurance and assessed the segments of the market in terms of risk and profitability. In close collaboration with both the underwriting and actuarial teams, we help them set future strategic goals for that line of business.
Rate pressure in the global commercial property market was a concern for a Lloyd’s Managing General Agent (MGA) with a large exposure to these risks. With an aim to improve their risk selection and mitigation procedures, they wanted to assess their historical book with a view to altering the mix of the business over the next few renewal cycles.
An extensive amount of data engineering, cleansing and exploration work was required in the initial stages of the project, combining additional data sources to enrich the data. Locations covered by each policy were available, but claims were linked to policies. Policy terms such as attachment points and limits were accounted for within the model.