A Markov Decision Model for Selecting Optimal Credit Control Policies

The rapid growth of consumer credit has created a need for improved credit control policies which result in lower total credit costs. This paper investigates one approach for achieving that objective. The credit control problem is formulated as one of developing optimal policies for an infinite horizon Markov decision model. The model utilizes standard financial data; it also requires the measurement of the costs and returns from alternative credit control policies. The Markov model is transformed into an equivalent linear program. A sample problem is solved and the resulting policies analyzed.