Dynamic Valuation of Delinquent Credit-Card Accounts
Naveed Chehrazi, Thomas A. Weber
Management Science · 2015 · Volume 61 · Issue 12
Abstract
This paper introduces a dynamic model of the stochastic repayment behavior exhibited by delinquent credit-card accounts. Based on this model, we construct a dynamic collectability score (DCS) that estimates the account-specific probability of collecting a given portion of the outstanding debt over any given time horizon. The model integrates a variety of information sources, including historical repayment data, account-specific, and time-varying macroeconomic covariates, as well as scheduled account-treatment actions. Two model-identification methods are examined, based on maximum-likelihood estimation and the generalized method of moments. The latter allows for an operational-statistics approach, combining model estimation and performance optimization by tailoring the estimation error to business-relevant loss functions. The DCS framework is applied to a large set of account-level repayment data. The improvements in classification and prediction performance compared to standard bank-internal scoring methods are found to be significant. This paper was accepted by Noah Gans, stochastic models and simulation .
Keywords
account valuation, consumer credit, collectability scoring, credit collections, GMM estimation, maximum-likelihood estimation, operational statistics, self-exciting point process
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