Discover Milliman Claim Variability BenchmarksTM

Milliman Claim Variability Benchmarks are new industry benchmarks to help assess the quality of stochastic unpaid claim distributions used for ERM and DFA, including correlations for aggregate distributions. The benchmarks also stochastically support deterministic ranges used for reserving.

Three new benchmarks

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Use LDF patterns, unpaid distributions, and correlation values as needed.

Accurate estimation

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Ensure you have sufficient risk-based capital for operating activities.

Tailored results

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Adapt benchmarks based on company size, development patterns, and more.

Benefits of the solution

  • Improve unpaid claim estimates

    Dynamically assess your assumptions using powerful guidelines.

  • Limited data often leads to underestimation of risk.

    Distribution and correlation benchmarks lead to a better understanding.

  • Match risk profile

    Get the reinsurance that’s right for your company and avoid tail underestimation.

  • Meet Board standards

    Align to industry-standard guidelines.

  • Increase competitiveness

    Match prices to claims risk to improve margins and meet market needs.

Key Features

  • The power of big data

    Massive amounts of data are used to back test models and adjust for biases across most major lines and all sizes of companies, based on 4,800 U.S companies for 16 lines of business over 9 years.

  • Works with familiar tools

    The benchmarks are available as a simple-to-use Excel add-on.

  • Meet company needs

    The solution can be adjusted for different development patterns, currencies and variance assumptions.

  • Succeed with your chosen approach

    Use with deterministic estimates to provide range information from industry data, and get reasonableness tests for stochastic estimates.

Milliman Pixel
Mark Shapland

mark.shapland@milliman.com

+971 4 386 6990

Ken Scalf

ken.scalf@milliman.com

+1 404 254 6705

Discover how you can improve risk management, pricing, and competitiveness with Milliman Claim Variability Benchmarks. Contact Ken Scalf or Mark Shapland today to learn more.

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