Traditionally, lenders have been evaluating their potential customers based on the credit scores received from the external credit bureaus. For instance, FICO scores are used in about 90% of consumer-lending decisions, according to CEB TowerGroup, a financial-services research firm. However, they may not be an accurate reflection of the creditworthiness of their customers. Today lenders need to enhance their credit scores with additional credit and collateral data to support analysis of complex loan applications.
Why Banks need to look beyond the conventional credit scoring agencies for Loan Underwriting?
Some of the issues associated with reaching accurate credit scores include:
- Credit reports provided by agencies may have incorrect or missing applicant data. In some cases,the applicant may not be using a credit card at all or may have an emergency medical bill due, which might lead to incorrect inferences being drawn from these credit reports
- New/updated credit information does not appear in credit reports as many creditors may not choose to report their accounts or sometimes updates may get reflected after as long as 90 days
- The traditional scoring models have less forecasting power than the new analytics based scoring models as the latter take into consideration the soft information as well
- Credit bureaus do not collect all available information which would impact credit score and loan price; income and cash flow management details are ignored
What lenders need today is an integrated solution incorporating underwriting automation and supporting analytics, thus improving the overall risk assessment of a given loan. The solution that banks need to consider should enhance their current scoring mechanisms. It should also provide the flexibility of a two–step evaluation- internal rating as well as external rating. As a first step, the solution should allow the bank to come up with an internal rating based on customer’s historical data or data present in the application. Once the applications have been filtered based on bank’s internal rating policies, those applications would then be evaluated on the basis of the credit scores provided by external credit rating agencies. The applications that fail the internal criteria might be rejected at the first stage itself, and may not need an external scoring check, thus minimizing the associated costs. All this is possible to be delivered by a platform which is flexible and agile and should help configure and modify lending processes as per the business needs.
Complement Credit Score Evaluation with Collateral and Other Risk Evaluations
Rising delinquencies have made lenders question Credit Scores as the only factor associated with loan defaults. Other important parameters that need to be considered are collateral risk and the product complexity. What is needed is a more comprehensive underwriting tool with enhanced credit information, new scoring models and updated credit analytics. The chosen solution should have the flexibility to allow banks to enter data collected from various sources and process it based on its internal policies. An agile rule-engine platform would come handy at this stage as it would not only permit the bank to configure the credit policies as per the nature of the business, but also modify it easily as per the dynamic market environment.
Lenders need a complete picture of the credit risk and not rely solely on the credit score provided by the bureau. They need to create/update the internal credit scoring model using a platform with configurable rules and ability to process data from multiple sources. It’s time to innovate the lending structure or banks may lose out on potentially worthy customers.