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OM Practice—Balancing Risk and Efficiency at a Major Commercial Bank

Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
Treasury Department, PPG Industries, Inc., Pittsburgh, Pennsylvania 15272
sk0a{at}andrew.cmu.edu
ns7{at}andrew.cmu.edu
esonmez{at}andrew.cmu.edu
kwest{at}ppg.com

Check processing institutions are being forced to downsize their workforce to cut cost and improve the efficiency of their operations as a result of continued growth of electronic payments, a consequence of the increasing popularity of debit/credit cards and use of online banking. For these institutions, these events are making more urgent the decision of how to staff a check-clearing house to trade off efficiency and the expected costs associated with the risks of delayed checks, which include fraud and float costs. In this paper, we discuss how a team of executives at a major commercial bank (CB) and Carnegie Mellon University students and faculty engaged in conducting a model-based study of the CB check-clearing operations. This project culminated in the development of a simulation optimization model to systematically analyze the nature of the highlighted risk efficiency trade-off at CB. The firm used the model recommendations to obtain operations downsizing guidelines for its senior managers during the implementation of a strategic workforce reduction program at their check-clearing house. The managerial insights from the team analysis, and the specific model-based recommendations, enabled CB executives to balance risk and efficiency while planning the reduction of their check-processing workforce.

Key Words: check processing; workforce sizing; worker cross-training; cost of risk; simulation optimization; math-programming-based lower bound; empirical research
History: Received: December 23, 2005; accepted: October 29, 2007.