An Algorithmic Model for Retail Credit Portfolio Segmentation

Journal of Risk Model Validation, Forthcoming

23 Pages Posted: 13 Mar 2013 Last revised: 28 May 2013

See all articles by Andy Yeh

Andy Yeh

Federal Reserve Banks - Federal Reserve Bank of San Francisco

Jose A. Lopez

Federal Reserve Bank of San Francisco

Date Written: March 13, 2013

Abstract

Under the new Basel bank capital framework, a bank must group its retail exposures into multiple segments with homogeneous risk characteristics. The U.S. regulatory agencies believe that a bank may use the internal models, including the loan-level risk parameter estimates such as PD and LGD, to group exposures into the resultant segments with homogeneous risk attributes. In contrast to the conventional decision tree method, we propose a new algorithmic technique for retail consumer loan portfolio segmentation. This new technique identifies the optimal number of segments, sorts the individual loan exposures into the various segments, and then leads to a greater degree of risk homogeneity in comparison to the baseline equal-bin and quantile-bin schemes. Furthermore, we analyze the Monte Carlo implied asset correlation values for the retail loan segments over time to help assess the implications for bank capital measurement. Our recommended method for retail credit portfolio segmentation results in some capital relief that serves as an incentive for the bank to invest in this alternative segmentation. This positive outcome accords with the core principle of statistical conservatism that is enshrined in the Basel regulatory requirements for bank capital measurement.

Keywords: Basel model development, Monte Carlo simulation, asymptotic single risk factor model, credit risk, segmentation, retail mortgage segmentation, k-means cluster analysis, risk capital management, asset correlation analysis

JEL Classification: D81, E44, G13, G17, G21, G32

Suggested Citation

Yeh, Andy and Lopez, Jose Antonio, An Algorithmic Model for Retail Credit Portfolio Segmentation (March 13, 2013). Journal of Risk Model Validation, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2232465

Andy Yeh (Contact Author)

Federal Reserve Banks - Federal Reserve Bank of San Francisco ( email )

United States

Jose Antonio Lopez

Federal Reserve Bank of San Francisco ( email )

101 Market Street
San Francisco, CA 94105
United States
415-977-3894 (Phone)
415-974-2168 (Fax)

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