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Adverse selection and non-take inference with coherent risk and response scoring

Author

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  • R M Oliver

    (University of California at Berkeley, Berkeley, CA, USA)

  • A M Thaker

    (InfoCentricity, Inc., Novato, CA, USA)

Abstract

The authors offer a mathematical model for adverse selection by individual borrowers based on preferences for offers and the default (Bad) or non-default (Good) status of booked accounts. We define the condition for borrower risk and response when there is no adverse selection (NAS). This definition provides us with a direct comparison between the prior and posterior conditional probabilities of default by an individual borrower who Takes an offer; this allows us to obtain estimates of differential response rates for individual borrowers and the Good/Bad odds for Take, Non-Take and Accept sub-populations. Performance of different response-risk segments allows us to compare price-driven risk elasticity and price-driven response elasticity in the presence of Good or Bad adverse selections; a special case applies when the borrower's capacity to repay is not an issue. We offer limited experimental results for selected price-risk segments where action-based risk and response scores are used to estimate borrower preferences. The critical role of Non-Take inference is described.

Suggested Citation

  • R M Oliver & A M Thaker, 2013. "Adverse selection and non-take inference with coherent risk and response scoring," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(1), pages 70-85, January.
    • Handle: RePEc:pal:jorsoc:v:64:y:2013:i:1:p:70-85
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