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A Statistical Diagnosis of Customer Risk-Ratings in Anti-Money Laundering Surveillance

Statistics and Public Policy, 2(1), 12-24 (2015)

36 Pages Posted: 9 Oct 2014 Last revised: 6 Jan 2016

Bhojnarine R. Rambharat

Office of the Comptroller of the Currency

Andrew John Tschirhart

Government of the United States of America - Office of the Comptroller of the Currency (OCC)

Date Written: May 21, 2014

Abstract

A statistical framework is presented to assess customer risk ratings used in anti-money laundering (AML) surveillance. We analyze data on a sample of 494 customers from a U.S. national bank where the customers are rated from Low to High over 13 time periods. We model these ratings using an ordinal panel data regression framework with random effects, utilizing a set of covariates provided by the bank. We derive the log-likelihood of the model and provide the maximum likelihood estimates (MLEs) of the model parameters. Our findings unveil key policy-related insights, based on the statistical model, about AML surveillance. We provide statistical evidence to support more granular monitoring of highly suspicious customers, which could optimize finite resources in bank operations. Furthermore, we provide two applications using these data, one concerning predictive inference and the other about log-linear modeling. Our analysis provides an approach to diagnose potential limitations with real-time AML surveillance systems. We argue that statistical diagnosis in AML surveillance has invaluable benefits within the micro-sphere of a single financial institution, and, more importantly, that these benefits extend to important public policy issues confronting the global community.

Keywords: Ordinal panel data, Investigation event, Predictive inference, Log-linear modeling, Financial crime policy

JEL Classification: C00, C23, J18

Suggested Citation

Rambharat, Bhojnarine R. and Tschirhart, Andrew John, A Statistical Diagnosis of Customer Risk-Ratings in Anti-Money Laundering Surveillance (May 21, 2014). Statistics and Public Policy, 2(1), 12-24 (2015). Available at SSRN: https://ssrn.com/abstract=2506614

Bhojnarine R. Rambharat (Contact Author)

Office of the Comptroller of the Currency ( email )

400 7th Street SW
Mail-stop 6E-2
Washington, DC 20219
United States

HOME PAGE: http://www.occ.gov/topics/economics/economics-staff/bios/ricky-rambharat-bio.html

Andrew John Tschirhart

Government of the United States of America - Office of the Comptroller of the Currency (OCC) ( email )

400 7th Street SW
Washington, DC 20219
United States

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