Introduction Mobility CU is a three-branch, $360M credit union based in DFW, Texas. Their early adoption of a data analytics culture makes them unique among similarly-sized credit unions. What they have in common with their peers, though, is their desire to improve car repo processes and decrease their losses. Car repossessions are at their highest level since 2009, and are up 16% from 2023 and 43% from 2022, reports Cox Automotive. And the state of Texas, where Mobility CU resides, has the second highest rate of car repossessions in the nation, second to California. Mobility’s CEO Ron Perry and VP of Lending Ruben DeLoera were interested in reviewing their current car repo processes and asked their data analyst to investigate, using the Gemineye Data Lakehouse and their collections integration. Challenging Assumptions with Objective Data There’s certainly no shortage of repo companies in Texas, and not all are created equal when it comes to payout. Historically, Mobility CU worked with repos who they had the best relationship with, which included a half-dozen organizations. But as repossessions grew, it made sense to audit their current relationships and question the old way of doing things. “Selling our repossessions is of big importance to us,” explains Chris Clifford, Data Analyst at Mobility CU. “The CEO and VP of Lending asked me to look at what were we actually getting from the auctions at an aggregate level. We needed to question all assumptions. Which auctions were the best bang for our buck?” Collections Integrations Proves Fruitful Mobility CU had just completed their collections integration with the Gemineye Data Lakehouse, which was the first step in auditing their repo relationships. Once the collections platform was integrated into the Gemineye Data Lakehouse, Mobility suddenly had insights into repo prices that they’ve never had access to before. “I looked at all our repossession cases and calculated the average of fees per repossession and the time between when we got the car and when it was sold”, says Clifford. “We wanted to know who was giving us the best percentage.” Clifford was able to create a report that looked at how various auction repossessions compare in terms of the average fees they charge and the amount they ultimately get at their auctions. This allowed the credit union to identify which companies to shift their business to. By switching repo companies, Mobility was able to save $100-$150 per car, and occasionally more. And with 15-20 repos per month, this one report saves the credit union between $18,000 and $36,000 a year. “A single report paid for the entire collections integration and then some. That’s pretty amazing!” exclaims Clifford. Creating a Data-Driven Culture for Success Transitioning to a data-driven culture takes time and patience, but the benefits can be transformative. Once the bar starts rolling, it becomes easier to incorporate data into strategic thinking and decisioning. This was exactly the case with Mobility CU. “It was so smart of the CEO and CLO to reassess our repo strategy,” says Clifford. “This report was originally intended to be a one-off, but we’ve discovered it’s totally doable to continue to use reports like this.” Mobility CU will continue to integrate reports like this into their departmental strategies. Clifford comments, “The true value of Gemineye is that y’all have lived up to the promise of being our analytics partner and not just another vendor, as evidenced in both the level and quality of service y’all have provided. Y’all have helped us all along our analytics journey even long after the initial implementation was done.” Conclusion While financial institutions look to increase their non-interest income, integrating their collections platform with the Gemineye Data Lakehouse proved quite helpful for Mobility CU. They were able to gain valuable insights into which car repo companies were providing the best payouts in a time when repos are high. What’s more, their transition to a data-driven organization has allowed them to challenge the status-quo and make decisions with facts rather than speculation. Discover More About the Capabilities of the Gemineye Data Lakehouse Interested in learning how the Gemineye Data Lakehouse can help you make data-driven decisions like Mobility CU? Browse the solutions we provide and teams we help!
