Vol. 2026, Issue 1, 2026July 16, 2026 EDT
Quantifying Social Inflation in Liability Insurance with Advanced Statistical Methods
Quantifying Social Inflation in Liability Insurance with Advanced Statistical Methods
Nuclear verdictsJury awardsLitigation costsTort costsClaim severityReinsuranceTail riskValue-at-Risk (VaR)Logistic regressionQuantile regression
Articles in Vol. 2026, Issue 1, 2026
Vol. 2026, Issue 1, 2026
- When the Past No Longer Predicts the Future: Reserving Considerations Under Social InflationKatherine PipkornAndy KlineBrian Brown
- Spectral Pricing Using Black ScholesDavid Brown
- Quantifying Social Inflation in Liability Insurance with Advanced Statistical MethodsTsz Chai FungLiang PengFang YangLie Ma
- Residual Development Factors: A New Loss Reserve DiagnosticChristopher E. Olson
- Insurance & Exchange Rate RiskJustin N. Smith
- When a Portfolio Reaches Sufficient ScaleJayson Farrell
- The Value of InsuranceRajesh SahasrabuddheZhenkai Zhu
- A Distribution-Based Recursive Extension of the Bornhuetter–Ferguson Method for Loss Ratio Estimation: Balancing Stability and ResponsivenessMitchel B Merberg
- Attribution of Loss Development Dynamics: A Bayesian Structural Time Series ApproachRoger Sarvate
- Method to Include New Business When Measuring the Rate Change of an Excess Casualty Insurance PortfolioThomas FiorilloNeil BodoffScott Lombardo
- Diagnosing Attribution Limits in Loss Triangles: An Open-Source, Scenario-Based Reserving WorkflowEytan Ellenberg
- A Practitioner’s Guide to Adjusting for “Limits Drift” in Experience RatingEric DyndaNeil BodoffAdam Carvalho
Fung, Tsz Chai, Liang Peng, Fang Yang, and Lie Ma. 2026. “Quantifying Social Inflation in Liability Insurance with Advanced Statistical Methods.” CAS Forum 2026 (1).