Should You Bank on that Boat Buyer?

Laurentian Bank creates online scoring models for dealer financing

Each year, Laurentian Bank receives thousands of requests through recreational vehicle dealers across Canada from consumers wanting to borrow money to purchase vehicles such as snowmobiles, ATVs, boats, RVs and motorcycles. Developing an accurate model to determine the risk of those loans and predict the possibility of payment defaults, quickly and accurately, is a huge task that is critical to the bank, dealers and consumers.

Laurentian Bank has turned to SAS Credit Scoring to help it develop a credit risk scorecard, an algorithmic model that takes credit, socioeconomic data and other information about an applicant and determines the risk level of that applicant in the form of a score. "Indirect vehicle loans is one of the fastest growing areas of our retail business," says Sylvain Fortier, the bank's Senior Manager for Retail Risk Management. "Our objective was to improve our use of the technological tools available for data exploitation and analysis that we needed to develop a scorecard internally. We wanted to develop a flexible system that would help us learn about our customers and business through the loan process."

Laurentian Bank began as the Montreal City and District Savings Bank in 1846. During a century and a half, it has grown into the seventh-largest chartered Schedule 1 bank in Canada with more than (CDN) $16 billion (US$12.9 billion) in assets. It offers competitive products and personalized services to meet the needs of individuals, small and medium-sized business, and independent financial advisers through its own distribution networks and independent financial intermediaries.

Scoring itself
The bank began looking at a credit rating solution for its vehicle loan business more than a year ago. In the past, it had mandated external firms to provide or create a scorecard model for the bank with its proprietary data or pooled data. As the vehicle loan business continued to grow, the bank determined it would be more efficient and cost-effective to do the scoring development internally.

Laurentian looked at a number of software packages but eventually chose SAS because of its flexibility. "The competing software was only a black box," says Fortier. "With SAS, we can change or adapt our analysis or an aspect of a problem at any stage in the process. By working internally we can make decisions along the way to make sure that the scoring model is the best it can be and is easy to implement."

Automatic scoring
With the scoring model available on the bank's intranet, dealers across the country can submit an application and get an almost instantaneous response to a loan request.

"The gains we made in just a few months have been very interesting," says Fortier. For example, automatic loan approvals nearly doubled. In only a few months, the bank will achieve a return on investment of 33 percent, 4 percent more than it anticipated at the start of the project. And it expects to reduce its losses on automotive loans by 8 percent on newly acquired loans, primarily from the accuracy of the model that SAS Credit Scoring has created.

"The quality and efficiency of the loan appraisal process has definitely improved from when scorecards were acquired from a vendor," says Fortier. "We've had good feedback from every level of the business and from the dealers. They are happier about the way we do business because they get answers to their loan requests more quickly. The model is definitely doing more than we expected at first."

Fortier says that the Bank now envisages developing credit scorecards for other areas of the bank's operations. "We are already planning to replace our existing scorecards for our retail personal loan business at our branches," he says. "In the next few years, all of our customers could have a risk profile associated with them."

According to Fortier, the knowledge that the bank has acquired about its customers during the scorecard project is being shared with other departments and will be very helpful in its business development activities.

Extra points for SAS Consulting
Fortier is also very pleased with the quality and professionalism of SAS consultants who helped in the development of the scorecard model. "They helped us make better use of the software to ensure we did everything in the best and most efficient way," says Fortier. "They made sure we avoided some pitfalls and reviewed every part of the project with us as it was completed."

Laurentian Bank's scorecard project has scored a top grade. "We've gained a lot of knowledge about our customers that we can replicate in future scorecard models," says Fortier. "The more we know about our customers, the more efficiently we can serve them."

The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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