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.
- Visual exploration of the policy data and concentrations of risk
- A number of simple dashboard-style slice-and-dice tools were built to assist future underwriting
- Identification of loss making segments
- Strategic underwriting objectives for renewal identified
- Reproducible research methods allows for full auditability of the data engineering and exploration work critical to the project
- Efficient data processing software avoided need for ‘big data’ infrastructure to perform analysis
- Location less important than expected for attritional losses
- Rate pressure had significantly eaten into expected profit of the book
- Number of market segments below attritional loss-cost
- Total premium written could be reduced without affecting profitability
KEY CLIENT BENEFITS
- Reproducible research methods understood within the business
- Improved audibility of work eased its take-up when revisited a year later
- Enabled strategic decision-making based on quantitative reasoning
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