Change Management Challenges In Fintech

Change management is never easy, especially in HIGHLY regulated industries like financial services. Here are 3 easy steps firms can use to ensure their FAs successfully adopt AI technology (and serve more clients better): First, some background: - I've spent 20+ years working at all levels of product development (from Development Lead to CTO to VP of Product Management) for companies such as Microsoft, Hearsay, and Twilio Now, even though new AI technology is *meant* to be easy to use – like an assistant that does its job well on autopilot – it can still feel disruptive for FAs who are used to working manually (eg. taking notes, filing documents, etc.). Plus, there are data privacy and security concerns that naturally come up when using this type of technology. This means that change management in a HIGHLY regulated industry like financial services has two requirements: one from the software front, and the other from the human front: - The AI tool must address data privacy concerns through clear communication and control over data use (which we focused on at Zocks | AI for Advisors) - FAs need to fully integrate the tool into their workflows, so they can serve more clients, faster and better Here are 3 steps firms can follow for seamless AI adoption: 1) Empower FAs with language/support Trust is super important between FAs and their clients. To foster that, it’s important for firm leaders to equip their FAs with the tools to confidently explain AI tools like Zocks to clients. For example: - What the tool does (Is it recording data? How is it being used?) - How to ask for permission from clients - Assure clients they’re in control and can opt-out if needed Empowering FAs to understand the tech at least ONE level deeper helps them confidently answer client questions, and ease the adoption process overall. 2) Remind FAs which steps to follow when using the tool There’s always a learning curve with new tools. So quite frankly, reminding FAs to turn on the tool during meetings goes a long way. In virtual settings, this is easier because the tool can join automatically, but in in-person settings, they must manually turn it on and off. 3) Allow FAs to build trust with the system During the transition period, it’s totally fine for FAs to rely on manual note-taking to cement information in their minds and double-check the AI's data. This is a HUGE part of how they build trust with the tool. But over time, as FAs get more comfortable, they’ll be able to rely more on the tool to capture data, especially in moments when important information is flowing in a conversation (eg. family life goals). The real value of AI is that FAs won’t need to stop mid-discussion and interrupt the flow of the conversation just to take detailed notes, and allow them to focus on the client’s needs instead. Any thoughts?

🌎 Transforming Traditional Banks and Credit Unions: Lessons from Experience and Insights for the Future 🌎 After 21 years with ING Direct and Tangerine across several countries—and working with tech and fintech firms since—I’ve seen how transparency, customer-centricity, and innovation can transform banking. Yet here we are in 2025, and many banks and credit unions still face the same challenges we tackled years ago. 🤔 Customer Satisfaction Is Still Low Capgemini’s 2025 Retail Banking Report shows only 26% of customers are satisfied with their experience. As 💯 Jim Marous put it, banks may not be seeing mass exits, but they’re facing silent attrition—customers quietly moving products to neobanks like Nubank, Revolut, Stripe, Robinhood, Chime, and SoFi. Why is progress so slow? 🤬 Where the Friction Lies 1. Legacy Systems – Outdated tech makes it hard to offer seamless, personalized experiences. 2. Regulations – Compliance slows innovation—but it doesn’t stop it. 3. Cultural Inertia – Resistance to change is deeply embedded. 4. Data Silos – Fragmented systems mean fragmented customer views. 5. Fintech Competition – Agile, digital-native players are redefining expectations. 💪 Let’s be clear—THESE ARE NOT BARRIERS. They’re frictions. Frictions can be solved. Some of us built banks in environments where regulators hadn’t even imagined branchless banking. 🚀 Strategies for Transformation 🚀 1. Culture First – Customer focus must be embedded in the culture. Break silos, reward collaboration. 2. Modern Tech – Move to flexible, cloud-based platforms. Use AI and data to personalize. 3. Agility – Embrace iterative development. Test, learn, improve—fast. 4. Fintech Collabs – Partner with or acquire innovators to accelerate capability. 5. Customer-First Design – Simplify processes. Build trust through transparency. 6. Engaged Teams – Empower employees. Happy teams create loyal customers. Final Thought This isn’t about knowing what to do—it’s about doing it. Change is possible. I’ve seen it. Led it. Delivered it. So can you. If you're a bank, credit union, neobank or fintech ready to make real progress, I’d love to help. Whether in a C-level role or as an advisor, I bring experience that turns strategy into impact. David Bradshaw Andrew Chau Phil Taylor, FICB/FCSI American Banker Aline Badr PCC Brenda Rideout Stacey Schwartz Michael Giller Michael Aceto Gaurav Singh Mark Nicholson

In an increasingly connected world, our best experiences quickly become our minimum expectation. Once we encounter a delightful experience in one aspect of our lives, enduring an inferior experience becomes unpalatable. A good example of this concept is currently playing out in the wealth management industry, where financial advisors are under more pressure to evolve. The well-documented great wealth transfer, demands for hyper-personalization from clients, democratization of private asset classes, and other trends are pushing RIAs and institutions to empower FAs with the tools needed to deliver clients the best-in-class experiences they expect to receive. The challenge: With the abundance of wealth tech startups and solutions entering the fray to enable FAs to meet these changes, how will advisors digest these tools successfully in their day to day activities, and how will large institutions and RIAs incorporate these solutions in their technology and compliance frameworks? Startups and established vendors that get market adoption will solve the FA's most pressing pain points and help them do more with less, while simultaneously nailing the client experience across the value chain: 1 / Prospecting: FAs need a consistent flow of new prospects, whether through warm referrals, workplace benefit opportunities, or inbound requests due to life event triggers or liquidity events. The role of fintech solutions to meaningfully impact prospecting seems elusive in a relationship-driven business, but barriers have been broken in similar industries such as real estate. 2 / Client onboarding: A world with one-click, automated onboarding and a single pane of glass for all client assets is a dream for FAs. Workflows to onboard clients and open accounts have improved with new platforms, but data input and lineage challenges still exist. For many firms, not-in-good-order (NIGO) applications are still a major issue, and the transfer of assets can be a clunky, slow process. 3 / Client engagement: CRM tools and automated comms have improved the ability to create client touch points, but FAs still need leading-edge solutions to stay top of mind for clients and reduce client churn beyond research reports and birthday alerts. 4 / Access to new asset classes: As private assets continue to be en vogue, wirehouses and RIAs have been running hard to meet this evolving client demand, with many falling short. The fintech ecosystem has made progress in democratizing access to private markets, but there is no shortage of opportunities to orchestrate and integrate this $11T opportunity into an FA's client offering. 5 / Holistic planning: With better connectivity and tools, the ultimate opportunity for FAs lies in the ability to provide differentiated planning and advice, including tax planning. To do so would require a suite of tools to enable real time tracking of assets, immediate flagging of tax ramifications of potential transactions, and scenario planning.

Microchanges: The Hidden Amplifiers of Change Fatigue Last week, I shared metrics for measuring organizational capacity. Based on some of the great things shared, I wanted to explore a critical but often invisible contributor to that fatigue: microchanges. While we track major transformations, it's the cumulative impact of dozens of small changes that often pushes teams past their capacity limits. ❓ What Exactly Are "Microchanges"? Microchanges are those seemingly minor shifts that individually don't warrant formal change management: - A new field added to a customer form - Updated approval workflows - UI tweaks after system upgrades - Policy "clarifications" and exceptions - Revised meeting cadences Each seems negligible, but collectively they create significant cognitive load. According to research from London Business School, employees in digital-forward financial organizations navigate an average of 32 microchanges monthly—most completely unmanaged. ✨ The Fatigue Multiplier Effect Remember those fatigue metrics we discussed? Microchanges amplify them in predictable ways: 1. They consume the "recovery periods" between major changes that your dashboard might show as "low-intensity" zones 2. They disproportionately impact certain roles—usually those already handling the most formal change initiatives 3. They create "change noise" that makes communication about significant initiatives harder to distinguish In one financial services transformation I supported, we discovered a good portion of the reported change fatigue stemmed not from the core system/process implementation but from the constellation of small adjustments happening simultaneously. 🔎Practical Microchange Management To address this hidden fatigue driver: 1. Conduct a Microchange Audit: Have teams log ALL changes, regardless of size, for two weeks. The results are often shocking. 2. Implement "Change Bundling": Group small changes into periodic, predictable releases rather than continuous trickles. 3. Create Department Microchange Calendars: Visualize and manage the total change load, including the small stuff. 4. Assign "Microchange Coordination" Responsibility: Designate someone to track, bundle and communicate minor changes. ⛓️💥 Connecting to Your Change Capacity Dashboard Expand your fatigue metrics to include: - Microchange volume as a separate measure - "Change fragmentation" score (ratio of major to micro changes) - Department-level microchange exposure metrics Organizations that manage both major transformations AND the microchange environment consistently demonstrate greater change resilience and faster benefit realization! What microchanges create the most fatigue in your organization? Have you found effective ways to manage them alongside your major transformation initiatives? #ChangeManagement #OrganizationalChange #MicrochangeManagement #DigitalTransformation #ChangeFatigue

These days I’m sure grateful for the Change Management work I did as a student at Harvard. The data is sobering. 👉 MIT’s NANDA study: 95% of generative AI pilots fail to move into production. 👉 McKinsey: 70% of initiatives remain stuck in development or expansion after a year. 👉 Abandonment: 17% of projects in 2024 → 42% in 2025. 👉 Scaling success: only 5–10% of companies ever get there. The technology is not the problem. The people, processes, and organizational structures are. That’s where John Kotter’s 8 Steps for Leading Change still feel urgent today. AI isn’t just a tool you stack on top of existing workflows. It requires rewiring how companies operate. Yet most organizations continue to treat AI adoption like a software upgrade rather than a deep transformation. ↳ Create Urgency → Leaders assume urgency is obvious. It’s not. AI must be framed with data and stories that make stakes clear: competitors will use efficiency to outscale you. ↳ Build a Guiding Coalition → Pilots run by IT alone fail. Cross-functional coalitions with visible champions succeed. ↳ Form a Strategic Vision → Saying “we’re investing in AI” is not a vision. Linking it to growth, efficiency, and innovation is. ↳ Remove Barriers → Resistance is natural. Job fears are real. Change management has to dismantle these barriers directly. ↳ Generate Short-Term Wins → Early ROI in back-office functions builds trust and momentum. Without visible wins, resistance hardens. ↳ Institute Change → AI sticks when embedded in hiring, training, incentives, and culture. Startups don’t wrestle with this. They scale with AI by avoiding new hires and redesigning work as they go. Large companies face the harder task: unlearning, rewiring, and rebuilding. The lesson from Kotter and from the data is the same: Transformation is not about the technology. It’s about change leadership. If we want AI to succeed inside large companies, we have to stop asking: ❌ “How do we scale the model?” ✅ “How do we scale trust, adoption, and organizational learning?” Three actions to drive forward now: ✅ Use data and stories to prove urgency at every level. ✅ Create early ROI wins and broadcast them widely. ✅ Embed AI into culture, not just IT, through hiring, training, and incentives. Do. Fail. Learn. Grow. Win. Repeat. Forever. ♻️Repost & follow John Brewton for content that helps. 📬 Subscribe to Operating by John Brewton for deep dives on the history and future of operating companies (🔗 in profile).

70% of finance transformations fail. Why? A few reasons stand out: 1. Lack of executive sponsorship. Any major change requires commitment from the top. Without it, transformation efforts lose momentum. 2. Poor change management. People need help adapting to new processes and technologies. Ignoring this human aspect of change leads to low adoption and wasted investments. 3. Disconnected systems. Point solutions often don't integrate well across the technology stack. This results in fragmented data and inefficient financial operations. 4. Unclear business objectives. Transformation efforts should directly support strategic goals. Otherwise, it's just technology for the sake of technology. -- The good news is that by addressing these challenges head-on, your transformation can drive real outcomes: 1. Secure executive buy-in from the start and communicate the "why" consistently. Help them see how finance can better support corporate strategy with new capabilities. 2. Involve your team early and get their input. Listen to their needs and concerns. With an inclusive approach, they'll be allies, not resistors. 3. Take an ecosystem view when evaluating new solutions. Seek platforms that consolidate data and unify financial processes on a single system. 4. Maintain a continuous improvement mindset. Finance transformation is an ongoing journey, not a one-time event. Build in feedback loops to course correct as needed. See, technology is just one piece of the puzzle. It all comes down to leadership, communication, and culture change. And when done right, your team will be ready and willing to embrace the future. How has your organization approached this challenge? What lessons have you learned along the way? Source: AICPA & CIMA P.S. I'm Julio Martínez, founder of Abacum. Follow me for daily FP&A, SaaS and business growth insights + personal lessons.