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By creating an environment where all Gemineye Data Lakehouse systems run through Databricks, we just have one gear in motion. In your standard data analytics program, multiple gears (various services, separation of database, compute, storage, and ingestion) are in motion, creating exponential inefficiencies in time, labor, and cost.
Our unique structure allows you to retain control of your data (like member definitions), rather than you having to conform to your vendor’s requirements. What’s more, The Gemineye Data Lakehouse brings in all data with an “as of” process date – meaning you can query exactly what the data looked like as of a given past date.
Don’t assume profitability based on “averages of averages”. Connect to your data at the most granular level including interchange on transactions and interest spreads on individual products.
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Powerful ML/Al-driven engagement,
segmentation, and predicitive actions
Definition Customization documents fully integrated into the solution and design to ensure your team knows exactly how all fields move from source to the data warehouse to the dashboards and reports.
We currently support over 75 integrations – even the ones that other data analytics providers won’t touch. Our integrations incorporate leading credit union and bank solutions, like consumer loan and mortgage originations, digital banking, CRM / MRM, third-party data vendors, and more.
Gemineye has been a critical partner for us in the migration away from legacy data software and structure. They helped modernize our data architecture and migrate to a cloud infrastructure. It has been a game-changer!
We currently support over 75 integrations – even the ones that other data analytics providers won’t touch. Our integrations incorporate leading credit union and bank solutions, like consumer loan and mortgage originations, digital banking, CRM / MRM, third-party data vendors, and more.
Why Data Analytics Matters Data analytics is essential for staying competitive in today’s competitive landscape. A recent study by Jack Henry found that 42% of credit unions prioritize leveraging data ...
Welcome to our very first edition of “A Day in the Life of a Data Analyst,” featuring the equally talented and down-to-earth Ann Ditlow, Data Analyst at 4Front CU. Ann ...
Bill has a deep background in the credit union industry. Throughout his robust career in the industry, Bill has utilized technology and data with finance/accounting to help credit unions and banks ...
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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!
Sandwich, Mass (January 9, 2026) – Looking to advance their data analytics strategy and reporting, $17.5B regional bank Third Federal Savings and Loan has partnered with Gemineye, a data analytics solution designed specifically for community banks and credit unions. With almost two dozen branches across Ohio and an additional 16 throughout Florida, Third Federal has been recognized for both their impressive customer service and lending capabilities. Their leadership team understood the importance of investing in cloud technologies and cutting-edge reporting tools to set themselves up for continued growth. Observing their proactive approach to data and technology – not just a “set it and forget it” strategy – makes it obvious as to why they are a leader in the financial services industry. “Through our partnership with Gemineye, we look forward to being able to elevate our analytics experience,” said Third Federal Chief Information Officer Mike Carfagna (pictured). “The exceptional and integrated reporting offered by the Gemineye team will give us growth opportunities far beyond what we have today, along with a seamless transition for us and our customers’ experience.” “Gemineye is an integration powerhouse, above all,” said Maggie Chopp, Director of Business Development at Gemineye. “Our unique architecture allows us to integrate with virtually any software, which is really incentivizing for evolving FIs like Third Federal. We are so excited to have them as part of the Gemineye Team!” About Third Federal Savings and Loan Third Federal is a leading provider of savings and mortgage products, that operates by a value system of love, trust, respect, a commitment to excellence and fun. Founded in Cleveland in 1938 as a mutual association by Ben and Gerome Stefanski, the Third Federal mission is to help people achieve the dream of home ownership and financial security. The company lends in 27 states and the District of Columbia, and is dedicated to serving consumers with competitive rates and outstanding service. As an equal housing lender, Third Federal has 21 branches in Northeast Ohio, mortgage loan offices in Columbus and Cincinnati, and 16 full-service branches throughout Florida. For more information on Third Federal, visit thirdfederal.com. See Gemineye’s Data Lakehouse in Action Interested in learning how the Gemineye Data Lakehouse can support your member and community needs like USCCU? Schedule a personalized discovery call to see how our platform can transform how your institution’s data program.
A Guide to Choosing the Best Data Analytics Structure for Your Financial Institution The decision whether to integrate a centralized analytics structure or a departmental analytics structure has induced plenty of handwringing among financial institution leaders. After all, it is a decision which will completely alter the foundation of their organization’s data analytics program. What You’ll Learn from This Whitepaper In this whitepaper written for non-technical decision-makers who have data analytics as a strategic priority, we’ll objectively explore: The two main types of data analytics structures – centralized and decentralized/departmental An objective comparison of the pros and cons for each The questions you need to be asking your team and the data you need to be collecting as you navigate towards your decision Why This Guide Matters for Credit Unions and Community Banks As data analytics continues to transition to a “nice to have” to a “need to have” across the financial services industry, it’s imperative to arm yourself with the information needed to make an informed, intentional decision, rather than one that is rushed or based on anecdotal evidence. Download this straightforward, fact-based guide today!
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