E-business Enterprise Credit Risk Evaluation Based on Markov Chain

Credit risk evaluation decisions are important for the e-business due to the high level of risk associated with wrong decisions. The process of making credit risk evaluation decision is complex and unstructured. Markov chain is known to perform reasonably well compared to alternate methods for this problem. In this work, we describe this method and the case of a successful application of it to e-business enterprise risk assessment. We built a state transmission probability matrix to analyze and predict the enterprise's future credit state. The application is tested on real-world data. We show that Markov chain can be very successful in evaluating and predicting e-business enterprise credit risk.