What is scoring ?
Credit scoring uses applicant/customer data to assess statistically the likelihood of a positive outcome to any financial risk.
For example, if an applicant can actually afford to repay a loan. In order to best respond to the ever increasing credit demand, credit scoring systems have evolved to become an integral part of the credit granting processes.
Credit scoring is based on the premise that behavior of new applicants for credit will closely resemble that of similar past applicants.
A good knowledge of existing and prospective customers and understanding their behavior allows enormous benefits. Such insight can be achieved through the use of profiling techniques, such as scoring. A valuable decision support tool, scoring enables lenders to analyze and measure customers, helping them to manage risk and build successful customer relationships.
Generic scorecard
Generic scorecards are modeled on a sample of applicant records that broadly match the target market.
This scorecard addresses a large number of prospects and credit types. It is also the ideal choice for lenders who do not have exiting data or who are targeting a new business sector.
Specific scorecard
Specific scorecards are modeled using the lender's own data obtained through its own customer base.
The specific scorecards have greater accuracy and relevancy to the lender and they aim at identifying the best customer for a certain product.
The proposed framework for Basel II compels the supervisors to ensure that the banks implement credit rating techniques that represent their particular risk profile. Neural Risk Management is currently meeting this objective in its deliveries to financial institutions.
Concomitant with any specific scorecard developed Neural Risk Management provides its customers with detailed analysis needed for BASEL II specific calculations.
Credit scoring uses applicant/customer data to assess statistically the likelihood of a positive outcome to any financial risk.