Managing credit risk is a major challenge for financial services companies. This task is made even more challenging with uncertainties in the economy and fluctuation in the job market. A major challenge for organizations is to manage their delinquency and bad debt while at the same time they try to retain their good customers through good credit management.

The Challenge:

A major US financial services company had recently acquired a multi-billion dollar portfolio and wanted to implement an effective portfolio management to minimize delinquency and to provide good customer services to its well paying customers. The company needed a solution that enabled the Risk Management group to monitor the behavior of individual customers in order to reduce delinquency and at the same time minimize its reserve requirements.


The Solution:

A team was set up to identify the key customer requirements and the metrics that would be used to measure success.
 

	One of the first task was to develop a data mart to be used by Risk Management and Marketing to foster collaborative analytics and decision making between these two functional groups. This was necessary because Marketing was cross-selling against this customer base while Risk was focusing on credit risk management.
	Predictive Behavioral Scoring Models were developed using internal account receivable data and external data to evaluate the credit risk of every customer and to identify likely delinquents. These models were supplemented with the company’s policy rules to implement new credit authorization and new credit line management.

The Benefits:

The benefits created by this work were clearly stated by the Risk Manager in the following statements:
 

	We have reduced our delinquencies and losses
	We have been able to provide optimum credit authorization and new credit lines to our valuable customers
	We can dynamically monitor our customers and make quick credit decisions
	We have increased our collection effectiveness As well as our revenue