A successful credit card company must be able to accurately assess its credit risk at any given time. Having an up-to-date picture of which clients may default on payments is critical to this process, not only amongst new applicants, but existing customers too.

Cornercard was using a rules-based system to drive its credit risk management processes. This was created around the company's own experience of delinquency, selecting data elements and creating rules to automate the credit decision process. However, while the rules-based system helped speed up the credit assessment process, Cornercard believed it did not provide a high enough degree of accuracy and effectiveness to the credit evaluation process.

The decision was made to reinforce and improve the performance of the credit risk management system by opting for a behaviour scoring solution. Such a system would be able to review thousands of credit risk data elements in order to find the most predictive data elements and develop models with which customers could be assessed. These data elements could then be weighted through scorecarding to further improve the effectiveness of the models used. Not only would this help Cornercard improve its credit risk management, but it would also help the company boost its bottom line.