Abstract

In this paper, we introduce models of sequential decision making in consumer lending. From the definition of adverse selection in static lending models, we show that homogenous borrowers take-up offers at different instances of time when faced with a sequence of loan offers. We postulate that bounded rationality and diverse decision heuristics used by consumers drive the decisions they make about credit offers. Under that postulate, we show how observation of early decisions in a sequence can be informative about later decisions and can, when coupled with a type of adverse selection, also inform credit risk. We show through two examples how lenders may use such information in setting their offer rates.

Highlights

  • In consumer lending, portfolio managers typically have access to a scorecard used to forecast default probability for each applicant

  • Bounded rationality In “Adverse selection” section, we considered the case of a portfolio manager repeatedly marketing a credit product to a non-take population

  • We explain this phenomenon through bounded rationality resulting in diverse decision heuristics used by consumers

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Summary

Introduction

Portfolio managers typically have access to a scorecard used to forecast default probability for each applicant. Scorecards are built using historical data on loan accounts and their respective performance data. The inputs into the scorecard include financial, demographic and other personal information about each applicant. The output of the scorecard is a real-valued score for each applicant, which can be mapped to a probability of default [see Hand and Henley (1997) for scorecard construction]. Portfolio managers may have access to a scorecard forecasting applicant responses to offers. Forecasts of default probabilities and response probabilities serve as inputs to business metric functions such as expected profit

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