|
Situation
Alpha Credit Belgium, a wholly owned subsidiary of Fortis Bank, is in the consumer credit business. The service provider offers both expiring credit (a fixed-amount loan providing the entire amount in one installment, for a fixed rate and term) and revolving credit (a form of financing that is selected if additional spending capacity is required for a longer period). In Belgium and Luxembourg, Alpha Credit is a major player in vehicle financing, providing loans through importers and dealer networks under their brand names. Alpha Credit also manages several of its own revolvingcredit products, such as Optiline and Rondo. In addition, it is a service supplier for other financial services organizations such as Fortis Bank, Bank van de Post, and Cora Hypermarkets.
Alpha Credit has three subsidiaries:
- Aremas, which is in the late-payments collection sector
- Nissan Finance, which provides motor financing for Nissan
- Genève Credit & Leasing, which offers consumer credit and vehicle financing in Switzerland
Challenge
In Belgium, more than 30 percent of vehicle financing packages are provided by the dealer, frequently in the form of a loan from market leader Alpha Credit. If the dealer knows exactly what the customer’s budget options are, it can propose a tailored offer made up of a car plus financing. In this situation, it is important to be able to forecast the credit risk accurately. Alpha Credit wanted to make such credit risks transparent to dealers and called on its Management Information System (MIS) officers for this purpose. So-called credit risk analyses have to be performed to assess a loan applicant. These analyses are carried out using models that the MIS department has developed in-house.
Solution
In 1993, Alpha Credit selected SPSS’ statistical products as the basis for credit analysis models, because these products could be used to execute the entire analysis process. Today, Alpha Credit’s MIS environment is constructed entirely of SPSS solutions.
Alpha Credit uses a range of solutions from the IBM SPSS Statistics family for credit-risk analysis. This enables the company to undertake detailed analysis, including planning, data collection, data access and management, analyses, and report generation and dissemination. In addition, Alpha Credit can create refined models and report results in easy-to-use formats.
Results
- Eighty to 90 percent of all loan applications can be accepted instantly, depending on the product, because the Alpha Credit model identifies them as low-risk. The remaining, high-risk applications are rejected or investigated further. This promotes efficiency and reduces the processing time for applications.
- The use of models for credit risk analysis means the process is automatic and requires much less intervention on the part of the lender
- The use of SPSS solutions makes ad hoc reporting possible
Development and monitoring of credit risk analysis
Alpha Credit primarily uses IBM SPSS Statistics for the development and monitoring of credit scores and to develop Basel II models and profitability models. The use of statistical tools to develop credit risk models remains within the MIS department’s competency. SPSS solutions enable Alpha Credit’s MIS department to perform even complex analyses, so that strategic policy decisions can be made rapidly. Based on these reports, lenders can then make sound credit decisions.
From credit application scores to behavior models
In the past 12 years, Alpha Credit has developed various models for credit application scores, seven of which are now in use. Although in the past Alpha Credit mainly worked with application scores—with new customers split into “good” and “bad” prospects—the service provider is increasingly focused on developing behavioral models, also referred to as predictive models. With the help of these models, Alpha Credit can anticipate likely customer behavior and decide more easily which form of financing is the most appropriate. Predictive models also make it easy to identify the customers who are likely to switch providers. As a result, lenders can make much more informed choices based on better insight into customer behavior. With the help of these models, Alpha Credit significantly reduces the number of defaulting payers and also offers better service to “good” customers.
The MIS department’s most recent project, completed at the end of 2004, was the development of Basel II models. To comply with Basel II, companies must have a better grasp of the information contained in their organizations and be able to distribute it internally. This data then has to be accessible to people who work with it. Firms like Alpha Credit have to invest in solutions that can extract data and make it transparent.
In the future, Alpha Credit plans to use IBM SPSS Statistics for retention, reactivation, and customer segmentation, among other initiatives. This change in direction is related to a shift in products. In the past, Alpha Credit primarily offered expiring credit, but it is now placing a greater emphasis on revolving credit.
|