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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.
Quorum chose to work with Brewster [CEO of Gemineye] for his ability to facilitate our individual needs and growth.
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 ...
Creating a consistent scorecard across departments can be a real challenge for credit unions and community banks. It’s rare to see even two departments from the same financial institution utilizing the same documents to measure their goals for the year. Often, the question is asked “What exactly are we trying to accomplish as an organization?” When there are misunderstandings and misinterpretations of the highest strategic goal in the organization, it’s bound to create conflicting priorities. The Problem with Vague Scorecard Metrics Your credit union’s annual strategic goal is to create positive net organic membership growth, ages 18-44. Seems straightforward enough, right? Let’s explore where there could be a misinterpretation of measuring this goal across departments. Organic: How do we define organic? Do we exclude indirect lending? Membership: How do we define membership? Do we exclude trust accounts, conservatorships, business accounts, and specialty accounts, political campaign accounts and inherited/beneficiary IRAs? Age: When do we determine age? What if a member turns 45 before the end of the year? Are they removed from this measurement even though they joined when they were 44? Growth: What is our data from the year prior? Is every department working off the same data points from the prior year? Alignment: Does each department have a consistent understanding of membership allocation across cost centers? We can see how a seemingly straightforward goal is now ripe with opportunities for misalignment. Department leaders could interpret the measurement of this goal very differently, creating employee outcomes that are pulling in different directions. Overcoming Unified Scorecard Miscommunications with Visibility A challenge we often observe among credit unions and community banks is the difficulty in actual aggregation and modeling of the data needed to produce a reliable metric. This is where having the necessary tooling like a robust data platform becomes key. One of our credit union clients features their four organizational strategic goal trends by month on every employee’s report landing page. Every employee in your organization, whether you have 10 or 1,000, should be able to explain what your unified goal is and be able to access a place where they can see the progress of the goal. The key here is visibility and repetition – and to remember that your employees have vastly different knowledge sets and perspectives based on their roles and tenure. Robust Data Modeling Mitigates Unified Scorecard Challenges From a data analytics tooling perspective, finding a data analytics solution that can provide a robust data modeling approach is critical to creating a unified scorecard. It’s important to have the ability to drill down by granular dimensions that are customizable to your own organization’s logic, such as: Date range Product category Cost center Employee Persona Engagement type If your organization doesn’t have access to these simple categorizations, you could be missing a key part of the scorecard picture. To learn more about creating operational alignment through data analytics, download our complimentary whitepaper. Gemineye’s modern data platform is designed to help credit unions and community banks manage, unify, and activate their data across teams and tools. From data hygiene to real-time analytics, Gemineye gives you the foundation to improve both operations, such as unified scorecards, and member experience. Schedule a personalized discovery call to see how our platform can transform how your institution stores, manages, and uses data.
As a financial institution—whether a bank or a credit union—you collect data constantly. From personal member information and transaction histories to engagement touchpoints and product performance stats, your internal systems rely on accurate, up-to-date data to function efficiently. But why should your members care about how you manage that data? Because your ability to deliver excellent service, personalize experiences, and build long-term trust depends on it. Simply collecting data isn’t enough. How you manage, clean, organize, and use that data directly impacts your members’ satisfaction and perception of your institution. Clean Data Drives Better Member Experiences One of the cornerstones of effective data management is data hygiene—keeping your records accurate, current, and relevant. This may sound basic, but it becomes increasingly complex as you grow and interact with thousands of members across multiple platforms. Outdated data creates friction. Sending communications to former members, contacting deceased individuals, or continuing outreach to closed accounts can lead to frustration and damage your reputation. Cleaning your data regularly ensures: You’re only reaching out to active, relevant contacts Sensitive circumstances (like deceased members) are handled respectfully Communications are timely, accurate, and appropriate Avoid Member Frustration with Smarter Targeting Nothing erodes confidence faster than irrelevant or incorrect messaging. Think of the last time you received a service reminder for a vehicle you no longer own. Now imagine your members receiving a loan promotion for a mortgage they’ve already paid off. Messy or outdated data leads to: Missed opportunities for meaningful engagement Wasted marketing spend on irrelevant outreach Member distrust in your institution’s systems and competence By investing in robust data governance practices, you ensure that members receive communications that are timely and valuable—reducing the risk of overselling or appearing out of touch. Use Data to Connect with Your Members Credit unions and community banks are built on relationships and local relevance. With proper data analytics and management, you can better understand what matters most to your members. For example, data may reveal a need for a stronger financial literacy program. Without this insight, well-intentioned messaging can miss the mark—or worse, come off as tone-deaf. Good data management enables your institution to: Identify member priorities and causes your members care about Build authentic connections through honest, real-world messaging Demonstrate your commitment to your members through education and financial literacy Data Management Is Member Experience Management In today’s digital-first world, data management isn’t just an IT or operations concern—it’s a member experience issue. Clean, well-managed data helps you anticipate needs, reduce friction, personalize services, and ultimately build stronger, longer-lasting relationships. Improve Member Experience with Gemineye’s Data Management Platform Data management isn’t just an operational task—it’s a core part of your member experience strategy. When your data is clean, current, and actionable, your institution can deliver more relevant communications, improve service delivery, and deepen trust. Gemineye’s modern data platform is designed to help credit unions and community banks manage, unify, and activate their data across teams and tools. From data hygiene to real-time analytics, Gemineye gives you the foundation to serve your members better—every step of the way. Schedule a personalized demo to see how our platform can transform how your institution stores, manages, and uses data—without the hard sell.
Sandwich, Mass (July 22nd, 2025) – Gemineye is delighted to announce the winner of their first ever Client Developer Award. This award represents the very best in data analytics application and innovative solutions to financial services’ pain points. The award was given to P1FCU, led by Annie Stuart (pictured), Senior Business Intelligence Analyst at the $2.2B, Lewiston, Idaho-based credit union. P1FCU has grown tremendously over the past decade and is now a financial leader in the Western Idaho region. The Gemineye Client Developer Award is based on several criteria, including innovation and creativity, technical excellence, impact on operations, and collaboration. “The Gemineye Developer Award was created because we are constantly impressed with the way our clients have adopted the Gemineye Lakehouse and gone on to build more tools and dashboards unique to their team,” said Maggie Chopp, Director of Business Development at Gemineye and creator of the Client Developer Award. “We wanted to find a way to recognize and reward the effort of these analysts, engineers, and architects, and the tangible impact they have on their credit union. We are proud to support the foundational technology – but even prouder to be an ongoing partner to these development teams.” P1FCU’s project submission featured a report that visualized how much time tellers at each branch were spending on operational activities. Clint Johnson, VP of Data and Analytics, Stuart, and the rest of the data team collaborated cross-departmentally to answer the age-old question that plagues financial institutions: “What’s actually happening at our credit union branches?” And with 26 branches – another one on the way early next year, understanding what operational needs were required of each branch was critical to the credit union’s success as they continued to grow. Stuart explained, “We really wanted to answer the question: How many people do we need in each branch? What are they doing with their time? What level of staff do we need?” The project revealed key insights about how personal opinion shapes what it means to be busy at the branch level. And when it comes to analyzing nuanced data like new branch performance, the Gemineye Data Lakehouse has the flexible structure to support these initiatives. VP of Data Analytics Johnson explained, “Having the right platform that’s flexible and capable of holding and reporting all your data is very convenient. The Gemineye Data Lakehouse is built on Microsoft Azure and Databricks, which allows us customization – We add to it constantly. It’s far faster than having a whole system in house on premise.” A big congratulations to P1FCU and the data team for their innovative and collaborative efforts in branch operations. For more information on P1FCU, visit their website or find them on social media. See Gemineye’s Data Lakehouse in Action Interested in learning how the Gemineye Data Lakehouse can support your operational needs like P1FCU? Schedule a personalized demo to see how our platform can transform how your institution stores, manages, and uses data.
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