Competition in the auto financing industry drives the need for creative and effective ways to meet and exceed customer expectations. The company’s Auto Fi­nancial Services (AFS) believes in the need to wow, and is constantly researching ways to stay ahead of its customers’ needs.

AFS, a global automotive finance company and one of the companies 28 businesses, is headquartered in Midwest. It operates in over 22 countries, and employs approxi­mately 1,200 people. It maintains more that $25 billion in assets, with 950,000 leased vehi­cles. This type of reach means the commitment to “wow” has to be considerable, well-researchedauto-financing approval-1 and successful.

Problem:

As a response to the competitive market and their own internal quest for quality, AFS went to the source and conducted customer surveys to help it narrow down a goal. The survey responses, cou­pled with the company’s wish to capture a greater portion of the auto financial services market, led AFS to a target: customer service needed to be revved-up. Because of the high volume of credit appli­cations, services were becoming bottlenecked and bogged down. Customer service goals were set to service customers more quickly, efficiently and effectively. It was evident application turn­around time and timely response of credit managers to the customer were the keys to success. Upper management and customers ex­pected middle management to solve these issues. To help solve this challenge, middle management execs turned to ProcessModel® simulation modeling.

Solution:

auto-financing approval-2Customers supplied a significant amount of information relating to the originations (credit) area, therefore man­agement decided to channel its efforts there. A cross-functional team was established to model the exist­ing credit process.

The surveys submitted by the AFS cus­tomer base identified three critical re­quirements:

  • turnaround time of applications
  • accessibility of credit managers
  • predictability of credit decisions

To simplify the process, the team nar­rowed its scope to model turnaround time and the use of the credit managers.

In order to understand the model, it’s necessary to understand the origination (credit or underwriting) process. It be­gins when an application for credit is received from the dealership via fax. Data entry personnel enter the ap­plication data (e.g., name of applicant, address, employer, social security num­ber) and request a credit bureau on the applicant. The application data and bu­reau information is then forwarded on to the credit manager. The credit manager reviews the bureau score and applica­tion data and then decides to either ap­prove or decline the application. That decision is faxed to the dealer.

Before the cross-functional team was established, originations management brainstormed and identified potential scenarios to improve the service pro­vided to dealers.

One area that management thought could be improved was making sure the work hours of credit managers reflected those of the customers. They also brainstormed that service might be en­hanced by combining prime and sub-prime credit manager teams. The proc­ess modeling software let the team put their ideas to the test.

The team modeled two different credit process scenarios. One scenario con­sisted of establishing credit manager regional teams aligned by time zone. The other, a “pod model,” modeled matching up credit manager schedules by sales force coverage along with combining the prime and sub-prime credit managers.

Results:Stock Photo

The team found that applied simulation modeling is accurate, scalable and ver­satile as long as input is precise. This fact drove the team to an even greater level of quality. For example, initial time estimates for various process steps that were input into the model were
simply not accurate. These measurements had to be replaced by more exact readings attained through stopwatch analysis. As the team became more versed with the process of applied simulation mod­eling, they found that ProcessModel offered them an invaluable tool to achieve greater quality–quicker and more accurately than with previous sys­tems. The system was even comprehen­sive enough to handle whole dimen­sions of a process, such as elaborate shift schedules for underwriters. The pod model re­duced turnaround time by 58% and in­creased credit manager usage. The simulation helped AFS understand and improve the process in record time.