Integrating Moody’s RMS™ cyber models and a targeted training program helped a leading global property and casualty (P&C) insurer enhance its cyber data, achieve risk-appropriate pricing, and improve its portfolio composition.
Key takeaways
- Achieved a 20%–25% reduction in gross loss costs across all return periods
- Boosted better risk selection
- Enhanced understanding of which factors were driving cyber losses
The challenge — enhance cyber underwriting and exposure management
A leading global provider of P&C (re)insurance wanted to enhance its cyber risk strategy to improve risk selection, ensure risk-appropriate pricing, reduce exposure levels, boost market share, and strengthen its cyber position.
The company had developed an in-house cyber risk model to better understand factors driving cyber losses. However, many firmographics critical to pricing cyber risk — such as industry, company size, and jurisdiction — were not explicitly captured in the exposure data, making it difficult to generate reliable results. Additionally, aggregated and incomplete reinsurance books made it challenging to run portfolios through a risk model to identify affirmative cyber accumulations.
The solution — integrate Moody’s cyber models and enrich data
Moody’s conducted a comprehensive training program with the company’s cyber team to ground it in the use of our cyber model applications. The models are designed to help users more effectively quantify, manage, and operationalize cyber risk and to establish a single view of risk across primary insurance and reinsurance books.
To address the incomplete exposure data, the native data enrichment tool in Moody’s cyber models was used to identify missing and incorrect values and supplement the dataset with accurate, company-specific information. Using Moody’s disaggregation engine on the reinsurance books, the company generated a modelable portfolio representative of both locations and coverages. By integrating the client’s available low-resolution exposure and policy data with Moody’s cyber industry exposure database, the company was able to conduct much more accurate exposure assessments.
The outcome — higher-resolution data providing a single view of risk
By introducing our cyber models, the company was able to enhance its overall cyber exposure data — allowing for better risk selection, maintaining risk-appropriate pricing, and improving overall portfolio composition.
Embedding high-resolution, accurate information into the underwriting framework helped the company improve underwriting profit and achieve a 20%-25% reduction in gross loss costs across all return periods. In addition, transparent access to the back-end model parameters and assumptions allowed the company to validate its results and understand what factors were driving cyber losses.
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Cyber risk
Moody’s can help you assess, quantify, and mitigate firmwide cyber risk and exposure and, importantly, integrate learnings across the business to inform key strategy decisions.