Method and system for estimating insurance loss reserves and confidence intervals using insurance policy and claim level detail predictive modeling
First Claim
1. A computerized method for predicting ultimate losses of an insurance policy, comprising the steps of storing policyholder and claim level data including insurer premium and insurer loss data in a data base, identifying at least one external data source of external variables predictive of ultimate losses of said insurance policy, identifying at least one internal data source of internal variables predictive of ultimate losses of said insurance policy, associating said external and internal variables with said policyholder and claim level data, evaluating said associated external and internal variables against said policyholder and claim level data to identify individual ones of said external and internal variables predictive of ultimate losses of said insurance policy, and creating a predictive statistical model based on said individual ones of said external and internal variables.
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Abstract
A computerized system and method for estimating insurance loss reserves and confidence intervals using insurance policy and claim level detail predictive modeling. Predictive models are applied to historical loss, premium and other insurer data, as well as external data, at the level of policy detail to predict ultimate losses and allocated loss adjustment expenses for a group of policies. From the aggregate of such ultimate losses, paid losses to date are subtracted to derive an estimate of loss reserves. Dynamic changes in a group of policies can be detected enabling evaluation of their impact on loss reserves. In addition, confidence intervals around the estimates can be estimated by sampling the policy-by-policy estimates of ultimate losses.
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45 Claims
- 1. A computerized method for predicting ultimate losses of an insurance policy, comprising the steps of storing policyholder and claim level data including insurer premium and insurer loss data in a data base, identifying at least one external data source of external variables predictive of ultimate losses of said insurance policy, identifying at least one internal data source of internal variables predictive of ultimate losses of said insurance policy, associating said external and internal variables with said policyholder and claim level data, evaluating said associated external and internal variables against said policyholder and claim level data to identify individual ones of said external and internal variables predictive of ultimate losses of said insurance policy, and creating a predictive statistical model based on said individual ones of said external and internal variables.
- 24. A system for predicting ultimate losses of an insurance policy, comprising a data base for storing policyholder and claim level data including insurer premium and insurer loss data, means for processing data from at least one external data source of external variables predictive of ultimate losses of said insurance policy and at least one internal data source of internal variables predictive of ultimate losses of said insurance policy, means for associating said external and internal variables with said policyholder and claim level data, means for evaluating said associated external and internal variables against said policyholder and claim level data to identify individual ones of said external and internal variables predictive of ultimate losses of said insurance policy, and means for generating a predictive statistical model based on said individual ones of said external and internal variables.
Specification