Setting Acquisition Strategy for Retail Customers
19 Pages Posted: 23 Jan 2011
Date Written: December 15, 2010
Having a powerful default prediction model is not sufficient to guarantee the efficiency of the acceptance process for retail customers. Setting appropriate acquisition strategies is essential in order to ensure that the bank is accepting applicants with the desired credit profile and is minimizing the cost of the acceptance process. Especially in the last ten years, banks have done significant investments in models and tools to automate the acceptance process and reduce the number of referred applications and consequently the number of analysts needed to manually assess the quality of the applicants. However, if the right strategy is not set, these investments may prove to be useless and only add more complexity to the application process. In this paper, we analyze the different alternative methodologies that can be applied to set an optimal credit acquisition strategy. When a credit scoring model is available, setting the credit acquisition strategy mainly consists in defining the appropriate cut-off score and then implementing it in the correct way. We improve upon the existing literature analyzing the issue also from a business perspective as we are convinced that the optimum cut-off value cannot be found without a careful consideration of each particular bank peculiarities (e.g. tolerance for risk, profit-loss objectives, recovery process costs and efficiency, possible marketing strategies). Finally, we test our conjectures on a sample of credit card applicants collected during the year 2007 by an Italian bank.
Keywords: Acquisition strategy, Cut-off; Scoring models, Credit approval, Risk Management
JEL Classification: G21, G28
Suggested Citation: Suggested Citation