Vol. 2017, 2017July 01, 2017 EDT
Reserving with Machine Learning: Applications for Loyalty Programs and Individual Insurance Claims
Reserving with Machine Learning: Applications for Loyalty Programs and Individual Insurance Claims
Len Llaguno, Manolis Bardis, Robert Chin, Christina L Gwilliam, Julie Hagerstrand, Evan Petzoldt,
Data MiningPredictive ModelingReserving MethodsIndividual Claims ReservingClaims TriageLoyalty Program LiabilityData OrganizationUltimate Redemption RateBreakage EstimationSnapshot Triangle
Articles in Vol. 2017, 2017
Vol. 2017, 2017
- A Cost of Capital Risk Margin Formula For Non-Life Insurance LiabilitiesGlenn G Meyers
- An Adaptation of the Classical CAPM to Insurance: The Weighted Insurance Pricing ModelEdward FurmanRiˇcardas Zitikis
- Compendium of Credit Risk ResourcesJean-Philippe BoucherMathieu BoudreaultJean-François Forest-Desaulniers
- The Mathematics of On-LevelingIan Deters
- An Alternative Approach to Credibility for Large Account and Excess of Loss Treaty PricingUri Korn
- Removing Bias- The SIMEX ProcedureThomas Struppeck
- Residual Loss Development and the UPRRichard L Vaughan
- Unbiased Development for Individual Claims - Taming the Wild Burning CostJoseph A Boor
- Minimum Bias, GLMs, and Credibility in the Context of Predictive ModelingChristopher Gerald GrossJonathan P Evans
- Reserving with Machine Learning: Applications for Loyalty Programs and Individual Insurance ClaimsLen LlagunoManolis BardisRobert ChinChristina L GwilliamJulie HagerstrandEvan Petzoldt
Llaguno, Len, Manolis Bardis, Robert Chin, Christina L Gwilliam, Julie Hagerstrand, and Evan Petzoldt. 2017. “Reserving with Machine Learning: Applications for Loyalty Programs and Individual Insurance Claims.” CAS Forum 2017 (July).