Selection bias and auditing policies for insurance claims

Jean Pinquet, Guillén Montserrat (mguillen@ub.edu) and Mercedes Ayuso
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Guillén Montserrat: CECO - Laboratoire d'économétrie de l'École polytechnique - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique

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Abstract: Selection bias results from a discrepancy between the range of estimation of a statistical model and its range of application. This is the case for fraud risk models, which are estimated on audited claims but applied on incoming claims in the design of auditing strategies. Now audited claims are a minority within the parent sample since they are chosen after a severe selection performed by claims adjusters. This paper presents a statistical approach which counteracts selection bias without using a random auditing strategy. A two equation model on audit and fraud (a bivariate probit model with censoring) is estimated on a sample of claims where the experts are left free to take the audit decision. The expected overestimation of fraud risk derived from a single equation model is corrected. Results are rather close to those obtained with a random auditing strategy, at the expense of some instability with respect to the regression components set. Then we compare auditing policies derived from the different approaches.

Date: 2007-04-19
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Citations: View citations in EconPapers (7)

Published in Journal of Risk and Insurance, 2007, 74 (2), pp.425-440

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Journal Article: Selection Bias and Auditing Policies for Insurance Claims (2007)
Working Paper: Selection bias and auditing policies for insurance claims (2007)
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