Dynamic Valuation of Delinquent Credit-Card Accounts

• 成果类型: Article
• 署名作者: Chehrazi, Naveed; Weber, Thomas A.
• 署名单位: University of Texas System; University of Texas Austin; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2015.2203
• 发表日期: 2015
• 页码: 3077-3096
• 关键词: account valuation; Consumer credit; collectability scoring; credit collections; GMM estimation; maximum-likelihood estimation; operational statistics; self-exciting point process

摘要

This paper introduces a dynamic model of the stochastic repayment behavior exhibited by delinquent creditcard 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.