Creating trust in data for credit union growth

People want to feel confident that their personal data is being handled responsibly. They’re asking questions like: What is my data being used for? Why do you need it? Can I trust you to keep it safe? But they usually don’t get clear answers… Privacy laws like GDPR and CCPA are designed to address these concerns but following the rules isn’t enough to earn trust. Customers want control and clarity. And unfortunately, many banks make the experience even harder with processes filled with pages of legal jargon that most people don’t understand. When customers feel unsure about how their data is being used, they hold back. They don’t share information freely. And without that data, it’s nearly impossible for financial institutions to offer services that feel personalized or relevant. And when banks can’t meet those expectations, loyalty starts to fade, and it becomes harder to retain customers in an increasingly competitive market. The solution lies in creating transparent, customer-centric privacy frameworks: – Simple, clear interfaces where customers can easily understand and manage their data sharing preferences. – Centralized systems that consistently apply customer choices across all services. – Real-time validation ensuring data use always aligns with customer consent. – Clear communication about how shared data creates better, more personalized experiences. When financial institutions implement these approaches, the results speak for themselves. Customer confidence rises, trust deepens, and more people feel comfortable engaging with personalized services. This is what building genuine trust looks like in practice. #privacy #customertrust #dataconsent #fintech

Recent client meetings have left me a bit stumped! Because I keep hearing the following: “We don’t trust our data.” It's not the first time I've heard it, and I bet it won’t be the last. The irony? Those same businesses were using data every single day to pay invoices, run supply chains, and make strategic calls. So it’s not really the data they mistrusted. It must be something deeper. So where does this mistrust come from? Sometimes it’s a cover for not liking what the numbers say (because numbers don’t bend to opinion). Other times, it’s really about trust in the data team rather than the data itself. Occasionally, it’s just become a lazy throwaway line. If organisations want to break this cycle, both leaders and data teams need to change the way they work together. Here’s a 5 point playbook that stops “data mistrust” in its tracks: 1. Define Once, Use Everywhere: agree common definitions for key metrics. Document them, make them visible, and hold teams accountable for sticking to them. Consistency builds confidence. 2. Show the Journey: make data lineage transparent. Leaders should see where a number originates, how it’s transformed, and why it ends up in a dashboard etc. Traceability removes suspicion. 3. Shared Accountability: data isn’t an “IT product.” It’s a joint effort. Business leaders must own the accuracy of inputs; data teams must own the quality of models and outputs. Co-ownership prevents finger-pointing. 4. Resolve Issues Quickly: don’t let data concerns fester. Implement visible feedback channels, track issues openly, and close them with clear communication. The faster issues are addressed, the stronger trust becomes. 5. Normalise Hard Truths: not all insights will be comfortable. That’s the point. Leaders must be ready to hear what the numbers say, and data teams must present them clearly. Data itself isn’t untrustworthy. It’s the behaviours, mindset, and responses around it that determine whether people believe it. So let’s stop hiding behind the lazy phrase “we don’t trust our data.” 👉 Business leaders are you really questioning the data, or just avoiding what it’s telling you? 👉 Data teams are you giving the business clarity, speed, and confidence, or just more numbers to argue over? Because until both sides stop passing the blame, “data mistrust” won’t go away, it will just keep undermining decisions. Mark Stouse Bill Schmarzo Malcolm Hawker Eddie Short Kyle Winterbottom Edosa Odaro Joe Reis Matthew Small Dan Everett

𝗧𝗵𝗲𝗿𝗲 𝗶𝘀 𝗮 𝗰𝗼𝗺𝗽𝗮𝗻𝘆 𝘀𝘁𝗼𝗿𝘆 𝗯𝗲𝗵𝗶𝗻𝗱 𝘁𝗵𝗲 𝗱𝗮𝘁𝗮 Data is the cornerstone of modern finance, but algorithms alone aren’t enough. Without context, knowing, and a focus on real outcomes, data risks becoming noise rather than a tool for smarter decisions. When the human element is overlooked, decisions lack one hundred of the input, opportunities are missed, and trust is eroded. This impacts everyone—lenders, banks, and the businesses they aim to support—leading to reduced impact. Here’s how you can balance data with a human touch to create smarter, more appropriate solutions: ▫️ 1. Knowing Client Needs: Pinpoint the unique challenges and goals of businesses. ▫️ 2. Use Predictive Analytics: get data to identify trends, risks, and opportunities. ▫️ 3. Incorporate Human Insights: Combine data-driven strategies with expert judgment and client feedback. ▫️ 4. Design appropriate Solutions: Make sure incentives benefit all stakeholders fairly. ▫️ 5. Build Long-Term Trust: Focus on transparency and collaboration to strengthen relationships. ▫️ 6. Refine Strategies Regularly: Continuously adapt based on evolving data and client needs. ▫️ 7. Blending analytics with human thoughts builds trust, creates growth, and ensures better outcomes. How are lenders integrating the human and data elements into their strategies? Let’s discuss below! #data #analytics #businessintelligence #datamining #smallbusiness #localbanks #lenders

The Dark Truth About Data Most Won't Admit: Most organizations treat data like a forbidden vault: • Collect everything blindly • Obscure the mechanics • Pray for trust But here's the reality - trust isn't given, it's earned through visibility. When you embrace data transparency, three powerful forces emerge: 1. Confidence Cascade Clear practices lead to deeper trust Deeper trust enables richer engagement Richer engagement yields superior insights 2. Protection Multiplier Visible processes catch issues early Early detection enables rapid response Rapid response prevents major breaches 3. Innovation Accelerator Open systems encourage bold experiments Experiments generate fast learning Learning creates breakthrough solutions The winners in today's landscape? Not those hoarding the most data. It's those who handle it with radical transparency. DFFT (Data Free Flow with Trust) isn't just another acronym. It's the bedrock of sustainable data operations in our connected world. First introduced at the 2019 G20 Osaka Summit, DFFT established the blueprint for trustworthy cross-border data flow while unlocking unprecedented economic potential. Because in our complex reality: • Secrecy breeds doubt • Transparency cultivates trust • Trust fuels exponential growth The mandate is clear: Build systems that explain themselves. Create processes that invite scrutiny. Establish practices that build confidence. Your data will flourish. Your users will commit. Your business will thrive. The future belongs to those who embrace transparency not as a burden, but as a competitive advantage. Are you ready to build systems that last through trust? Share if you believe in creating transparent data ecosystems that endure. #DataTransparency #DFFT #DataTrust #Innovation