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Seow, H.-V. and Thomas, L.C. (2006) Using Adaptive Learning in Credit Scoring to Estimate Take-Up Probability Distribution. European Journal of Operational Research, 173, 880-892.
https://doi.org/10.1016/j.ejor.2005.06.058

has been cited by the following article:

• TITLE: Dynamic Programming for Estimating Acceptance Probability of Credit Card Products

  AUTHORS: Lai Soon Lee, Ya Mei Tee, Hsin Vonn Seow

  KEYWORDS: Credit Card, Credit Scoring, Dynamic Programming, Profitability

  JOURNAL NAME: Journal of Computer and Communications, Vol.5 No.14, December 29, 2017

  ABSTRACT: Banks have many variants of a product which they can offer to their customers. For example, a credit card can have different interest rates. So determining which variants of a product to offer to the new customers and having some indication on acceptance probability will aid with the profit optimisation for the banks. In this paper, the authors look at a model for maximisation of the profit looking at the past information via implementation of the dynamic programming model with elements of Bayesian updating. Numerical results are presented of multiple variants of a credit card product with the model providing the best offer for the maximum profit and acceptance probability. The product chosen is a credit card with different interest rates.