Automated credit-scoring systems are either generic or custom. A generic credit scoring system, such as the FICO model used by the vast majority of US grantors of credit, makes use of data from credit bureaus together with customer data to calculate a score to predict the likelihood of default on a new account. A custom credit scoring system typically utilizes both credit bureau data and other data from a credit application and is developed by the creditor (lender, lessor) based on the historical performance of its own credit portfolio.
| FICO Score-Interest – Example | |||
|---|---|---|---|
| FICO Score | Interest Rate | Monthly Payment | Total Interest Paid |
| ≥ 760 | 3485% | $896 | $112,710 |
| 700-759 | 3706% | $921 | $131,648 |
| 680-699 | 3883% | $941 | $138,900 |
| 660-679 | 4096% | $966 | $147,736 |
| 640-659 | 4525% | $1,016 | $165,884 |
| 620-639 | 5069% | $1,082 | $189,553 |
Many lessors use credit-scoring systems for automated underwriting. Automated underwriting expedites credit approval by allowing the automated acceptance or rejection of a large number of applications in accordance with the underwriting guidelines. Use of automated credit-scoring systems in credit and lease underwriting improves the ability to model and predict asset portfolio performance and allows for the underwriting of a greater volume of loans and leases for asset-backed securities.
| Credit Application ↓ | ||
|---|---|---|
| Credit Bureau Information → | Application Processing → | Business Decision |
| Consumer Bureau Information ↑ | ||