Selection bias and auditing policies for insurance claims

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      <subfield code="c">Jean Pinquet, Mercedes Ayuso, Montserrat Guillén</subfield>
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      <subfield code="a">This article presents a statistical approach that counteracts selection bias without using a random auditing strategy. A two-equation model for audit and fraud (a bivariate probit model with censoring) was estimated on a sample of suspicious claims for the experts was left free to take the audit decision. The expected overestimation of fraud risk derived from a single-equation model was corrected. Results were rather close to those obtained with a random auditing strategy, at the expense of some instability with respect to the regression components set. </subfield>
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      <subfield code="a">The Journal of risk and insurance</subfield>
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      <subfield code="t">The Journal of risk and insurance</subfield>
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      <subfield code="g">Vol. 74, nº 2, 2007 ;  p. 425-440</subfield>
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