MSU Federal Credit Union (MSUFCU), the world’s largest university-based credit union serves both Michigan State University and Oakland University communities. Founded in 1937 MSUFCU has 15 branches, over 205,000 members, more than $2.9 billion in assets, and over 640 employees.
Michigan State University Federal Credit Union Proves Need for Business Intelligence by Making Data Actionable
As early adopters of Symitar’s Advanced Reporting for Credit Unions (ARCU) there was little knowledge or support available to guide MSUFCU to find the best use of this platform. They knew they had to get the data from the core banking systems into SQL and automate their reporting, but the more difficult question was “What is our best first step?”
HOW DO WE MOVE FORWARD?
After meeting with CFS Consulting Group, MSUFCU realized that CFS was one of very few technology partners who had experience with ARCU and knew how to apply it to solve the unique challenges faced by credit unions. CFS analyzed and identified workflows at the credit union and the team decided that the D.A.V.E. project was a great option given its value to the business units.
The D.A.V.E. member process stands for:
- Debit – member has an active debit card
- Auto – member has an open auto loan
- Visa – member has an active Visa credit card
- E-statement – member subscribes to electronic statements
This profile represents MSUFCU’s most engaged members. The business goal was to identify the number of D.A.V.E. members, as well as the number of members just one or two services away from being classified as a D.A.V.E. member. The process for reporting on D.A.V.E. performance was both manual and time-consuming, which impacted the timeliness of the report. The accuracy of the information was also an issue due to the manual nature in which the data was compiled.
In addition, MSUFCU utilized FICS for servicing its mortgages. Allocating income and expenses for FICS was a painstaking manual process. Data for these loans was not stored in the core system and therefore not stored in ARCU. To create a custom consolidated income statement report, data from FICS had to be integrated into ARCU before developing and populating the custom income statement.
The Challenge Begins
As CFS culled through the membership data and reports, they realized that the number of D.A.V.E. members counted in ARCU didn’t match the number of members on any of the existing reports from the core system. It became apparent that more than a dozen different definitions of a member existed. This sparked a lengthy internal debate between business units to answer the question “What is a member?” Each unit was using their own definition specific to their unit’s reports. Compromise was finally achieved, but more importantly, one global definition of a member was determined.
The subsequent development and automation of the D.A.V.E. reports went smoothly from there. Ryan Olin, data analyst at MSUFCU confides that he expected the project to be quite difficult but due to CFS’s experience with Business Intelligence, the products involved and credit unions, they kept MSUFCU on the right path and avoided any pitfalls.
The other part of the engagement — the Consolidated Income Statement — was a critical report for the credit union. The first step was for CFS to integrate FICS information into ARCU using its Mortgage Data Connector for ARCU for FICS. Next, CFS provided development and mentoring of the MSUFCU staff to help them learn some of the complex reporting techniques used to deliver this report.