Objectives

The analysis assists businesses and banks in protecting their assets from the deterioration in business creditworthiness and consumer loan defaults. By reducing credit exposure and making collection strategies more effective, bad debt expense is minimized. Results from the analysis can be used by management to meet its credit risk objectives in a declining sales environment and a global recession.

The following chart illustrates the key contributors to bank loan defaults.

Analysis and Financial Data

The following indicators and tests are applied to identify problem accounts and prioritize collection efforts:

• Financial information used to assess current state includes A/R Aging, average collection times, A/R balances and history, Days Past Due, credit policy, credit terms, previous loan defaults, years with current employer, debt to income ratio, etc.
• Other factors contributing to delays in payment on the commercial side (billing errors, quality deficiencies, and delivery problems) are also analyzed for corrective action.
• Credit risk models are built using the most important predictors of default as well as the relationships between those predictors.
• In addition to probability of default, delinquencies are also prioritized by the amount of potential loss to identifying those accounts or individuals needing to be worked first and most aggressively.
• Models continuously monitor changing financial conditions and billing status (D&B financial data and individual credit bureau reports can also be used in monitoring).

Benefits

The benefits that can be realized from utilizing this solution:

• Credit risk modeling identifies delinquent accounts and gauges the severity earlier, enabling the collection efforts to be more successful.
• Credit risk model can be updated with new financial data continuously, thus maintaining performance during rapid changes in business conditions.