Common Obstacles in Financial Services Innovation

𝐅𝐢𝐧𝐚𝐧𝐜𝐢𝐚𝐥 𝐒𝐞𝐫𝐯𝐢𝐜𝐞𝐬: 𝐀𝐈 𝐀𝐝𝐨𝐩𝐭𝐢𝐨𝐧 𝐈𝐬 𝐒𝐮𝐫𝐠𝐢𝐧𝐠, 𝐁𝐮𝐭 𝐕𝐚𝐥𝐮𝐞 𝐈𝐬𝐧’𝐭 𝐊𝐞𝐞𝐩𝐢𝐧𝐠 𝐔𝐩 Banks are racing to deploy AI, yet most aren’t getting the results they expected. As of Q3 2025, 43% of global banks report internal AI deployments. But a major 2025 study found over 70% of companies struggle to convert AI investment into real business value. The gap between deployment and outcome reflects a deeper issue: complexity, risk, and limited visibility across the AI ecosystem. 𝐊𝐞𝐲 𝐀𝐈 𝐓𝐫𝐞𝐧𝐝𝐬 𝐑𝐞𝐬𝐡𝐚𝐩𝐢𝐧𝐠 𝐭𝐡𝐞 𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐲 • Real-time fraud and crime detection: Nearly 90% of FIs now use AI for AML, identity risk, and transaction monitoring, improving detection, but increasing monitoring and compliance requirements. • Automated underwriting and decisioning: The global AI in Lending market is growing at 26.6% CAGR, with some banks reporting 50–75% faster decision times. But more automation also means more decision nodes, data pathways, and model dependencies. • GenAI across compliance and operations: 75% of banks are exploring or deploying GenAI for KYC, document processing, and customer operations. More models = more efficiency and exponentially more governance demands. 𝐏𝐚𝐢𝐧 𝐏𝐨𝐢𝐧𝐭𝐬 & 𝐑𝐢𝐬𝐤𝐬 •Shadow AI and Model Sprawl: Teams deploy models independently across fraud, credit, and compliance, creating inconsistent decisions and governance gaps. • Data governance and regulatory exposure: Financial data moving across multiple systems without lineage increases AML, GDPR, and consumer-protection risk. • Model drift and silent accuracy decay: Fraud patterns evolve quickly. A model performing well last quarter may miss new attack vectors today. • Trust and explainability gaps: AI-driven denials and flags require transparency. Without it, regulatory and customer trust erode. 𝐖𝐡𝐚𝐭 𝐁𝐅𝐒𝐈 𝐋𝐞𝐚𝐝𝐞𝐫𝐬 𝐒𝐡𝐨𝐮𝐥𝐝 𝐃𝐨 𝐍𝐨𝐰 👉 Establish a unified, enterprise-wide AI governance layer that inventories every model, agent, data flow, and third-party tool. This layer should provide: • Model lineage • Runtime observability • Version control • Data access logs • Risk scoring Visibility is the foundation of safe, compliant, and scalable AI. Are you facing model sprawl, governance/compliance risk, or fragmented AI security fabric protects the enterprise AI layer and can help you manage and scale AI with trust and transparency. #BFSI #FinancialServices #AISecurity #AIGovernance #RiskManagement

The reality for Payment Companies is, you do not have time. No, this isn’t a doomsday prediction—it’s a wake-up call. Payment companies (Paytechs) are at risk of missing out on transformative top-line and bottom-line gains by hesitating on GenAI adoption. What’s holding them back? According to the BCG Global Payments Report 2024, three major roadblocks constrain established companies: 1️⃣ Waiting for Certainty in the Business Case: 85% of financial services firms believe GenAI will be transformational. Yet, 74% struggle to define a clear ROI. 2️⃣ Investment Concerns: Just 26% of firms allocate significant innovation budgets to GenAI. Many fear the challenge of explaining long-term benefits to investors while balancing short-term growth. 3️⃣ Inadequate Tools and Resources: Only 18% have a defined GenAI strategy. A mere 7% have delivery teams with operational KPIs in place. But here’s the game-changer: Leading players aren’t waiting—they’re leveraging GenAI to disrupt the payments landscape: 1/ Klarna: GenAI handles 66% of customer service chats, equating to 700 employees. Resolution times dropped from 11 to 2 minutes, driving $40M in projected bottom-line improvements for 2024. 2/ Stripe: Its GenAI-powered developer portal has made it the top choice in acquiring. A multifunctional search bar summarizes documents and answers developer queries in seconds. 3/ MasterCard & Visa: GenAI enhances fraud detection, redefining the fight against financial crime. Four key opportunities stand out: 1️⃣ Customer Service & Operations: Accelerate resolutions, slash costs by up to 70%. 2️⃣ Sales & Marketing: Hyperpersonalized outreach turns “markets of one” into a reality. 3️⃣ Compliance: Real-time KYC and automated documentation redefine regulatory readiness. 4️⃣ Assisted Coding: Faster prototyping, testing, and delivery. The Time to Act Is Now While the leap of faith may seem daunting, it is essential for businesses to stay ahead. Here’s why waiting is not an option: 1/ Perfection is the enemy of progress. Companies holding out for flawless use cases risk falling further behind. Embracing continuous improvement not only accelerates institutional learning but also drives faster margin growth and business model differentiation. 2/ Build strong foundations: Strengthen data structures, acquire AI foundational AI applications, integrate core processes and prioirtise upskilling of the workforce 3/ Lead with responsibility. GenAI comes with risks—bias, errors, and intellectual property concerns. Adopting a holistic, responsible AI policy framework is non-negotiable. Yet, only 13% of companies have acted. By championing responsibility, businesses not only mitigate risks but also enhance compliance and trust. The message is clear: delaying GenAI adoption is not just a missed opportunity—it’s a competitive threat. The time to act is not yesterday, not tomorrow, but today and NOW. Are you ready to take the leap?

Banks talk about innovation. But how many actually execute it? For years, I've seen banks struggle to turn innovation into action. They know they need to evolve, but the roadblocks are everywhere: 🚧 Fear of fintech competition: Instead of seeing fintechs as enablers, they see them as threats. 🚧 Overcomplicated pilots: Too many internal hurdles stall momentum before innovation can even take off. 🚧 Lack of clear success metrics: Without defined KPIs, how do you know if your innovation efforts are working? But here is the truth: Innovation isn't just a project - it's a *strategy* Thats why I created the Banking Innovation Roadmap - a simple, tactical framework to help banks move from concept to market leadership. This isn't about adding another buzzword to your strategy - it's about real execution. A strategic approach to innovation includes 👇 ✅ Discovery & Roadmapping: Understanding your bank's goals and aligning innovation to real business outcomes. ✅ Proof of Concept Development: Testing real solutions with fintech partners in a way that's controlled and measurable. ✅ Strategic Partnerships: Banks, fintechs, and organizations like FIS coming together to create new solutions that don't exist today (ahem, FIS + Affirm collab!) ✅ Modernization & Open Banking: Without the right infrastructure, innovation can't scale. ✅ Market Insights & Thought Leadership: Staying ahead of trends and leveraging industry expertise to guide decision-making. The banks that succeed don't wait for innovation to happen - they structure it, measure it, and operationalize it. I'll be diving more into this framework as I continue to iterate it. Most importantly: I WANT TO HEAR FROM YOU! Am I missing anything? What's the biggest roadblock you see when banks try to innovate? Drop your thoughts in the comments! #bankinginnovation #fintech #innovationstrategy

Your organization says it wants innovation. Your processes suggest otherwise. I watched a brilliant executive spend 6 weeks getting approval to test a $50/month software tool. By the time she got the green light, two competitors had already deployed similar solutions and moved ahead. This isn’t stupidity. It’s institutional logic taken to its absurd conclusion. Here’s what’s really happening: Every approval layer was added for good reasons. Every committee was formed to prevent real disasters. Every process was implemented to solve actual problems. But collectively, they’ve created something no one intended: organizations so protected from making bad decisions that they can’t make ANY decisions. The “We Already Have a Process” Problem Walk into any corporate meeting about innovation and listen to the language: • “How does this align with our existing governance framework?” • “What’s the ROI justification for deviating from proven methodologies?” • “We need to ensure this integrates with our current compliance requirements.” These aren’t questions. They’re defensive mantras. The underlying message is clear: If your innovation doesn’t fit our existing framework, the problem isn’t with the framework—it’s with your innovation. The Expert Authority Trap The CIO who built their career preventing security breaches. The CFO who optimized cost structures. The Legal counsel who knows every compliance pitfall. These aren’t obstructionist bureaucrats. They’re experts whose professional identity depends on understanding why things might go wrong. But expertise optimized for preventing known problems becomes a barrier to discovering unknown opportunities. What Actually Works The organizations winning this game don’t eliminate their governance systems—they create parallel tracks. → High-risk decisions get rigorous 6-week evaluations → Low-risk experiments get 6-day pilot approvals → Different types of innovation get different types of oversight The Real Challenge This isn’t about process—it’s about identity. When systems change, people must grapple with fundamental questions: What’s my role? What’s my value? Who am I in this new world? The IT professional trained to prevent problems must learn to enable possibilities. The finance analyst who eliminated costs must develop intuition about when spending money to learn is the most economical choice. The Bottom Line Organizations that thrive in the next decade won’t choose between innovation and control. They’ll master both simultaneously. They’ll develop what I call “institutional ambidexterity”—the ability to be stable AND adaptive, careful AND experimental, systematic AND creative. The question isn’t whether your organization can change. It’s whether your organization can learn to change intelligently. What’s the biggest innovation killer in your organization? Share your story in the comments—I read every one.

The Elephant in the Room: If Embedded Payments Are So Great, Why Are Some Struggling to Monetize Them? 🐘📉 In my last two posts, we explored how embedded payments continue to be a critical SaaS growth lever and why finding a true payments partner is essential. But let’s take off those rose colored glasses for a minute. As a CMO talking to peers across the ISV space, I hear the same frustrations over and over. Monetizing and maximizing the value of embedded payments looks easy on paper, but the operational reality is complex. If your platform is struggling to gain traction with its embedded finance offerings, you aren't alone. Industry data shows that ISVs are hitting four major roadblocks: 🚧 The Compliance & Security Burden: This is the #1 obstacle. A staggering 82% of ISVs cite regulatory/compliance requirements and security/risk management as their primary concerns preventing them from fully supporting embedded payments. Software companies want to build great software, not become compliance officers. 🚧 Integration & Operational Friction: Too many payment providers hand over developer docs and disappear. In reality, many ISV teams report integration timelines dragging out for four months or longer. If you lack the internal resources or technology to handle payment operations, the project stalls before it even begins. 🚧 Opaque Pricing & Statements: Trust is everything in a partnership. Yet, over half of ISVs report experiencing a lack of pricing transparency and optionality from their payment providers. Confusing statements and hidden fees make it nearly impossible for finance and marketing leaders to forecast revenue confidently or price competitively. 🚧 The Go-To-Market Gap: You can build the slickest checkout experience in the world, but if your provider delivers weak onboarding and minimal sales or marketing support, adoption will flatline if it takes off at all. It’s extremely difficult to market a new payments feature when your provider offers limited roadmap visibility and a slow innovation cadence. The CMO Takeaway: Treating payments purely as an API plug-in is a recipe for failure. To actually capture the revenue (and value) upside, ISVs need partners who take on the heavy lifting of compliance, provide low-friction migrations, offer crystal-clear commercial models, and actively co-market. We need to stop accepting "documentation-only" support and start demanding real strategic partnerships. SaaS leaders—which of these pain points is hitting your organization the hardest right now? Or is there another hurdle keeping you from maximizing your payments revenue? Let's continue the conversation in the comments! 👇 #SaaS #EmbeddedFinance #PaymentProcessing #GoToMarket #CMO #FintechPartnerships #ISV #ProductLedGrowth #RevenueOperations

An interesting and candid conversations in London this week was with the leadership team of a rapidly scaling European bank that is going to RFP to replace their current GRC platform in 2026 and wanted my insights on whom to look at — right at the moment where fintech pragmatism collides with regulated-bank reality 🏦⚖️. What became clear very quickly is something I’m seeing across financial services: early GRC decisions made for speed and cost eventually meet the hard limits of scale, complexity, and regulatory expectation. What worked at one stage of growth no longer holds when the organization expands across borders, deepens its ecosystem, and puts far more of its reputation on the line. A few themes from the discussion really stood out 👇 🔍 Ecosystem and third-party risk has become existential. When your business model depends on partners and clients operating under your banking license, your risk perimeter expands dramatically. Initial onboarding due diligence is often strong — but ongoing assurance and monitoring struggle to keep pace. 👥 First-line ownership is still the biggest cultural hurdle. Many organizations say the first line “owns” risk, but the reality is that second-line teams still do most of the heavy lifting. If technology doesn’t make risk intuitive and visible for the first line, accountability never truly shifts. 🔗 Siloed risk views don’t scale. Vertical, function-by-function risk management quickly breaks down in complex environments. There is growing demand for process-based, cross-functional visibility that mirrors how the business actually runs — not how org charts are drawn. 🧭 User experience is no longer a “nice to have.” If people don’t want to use the platform, risk management stays centralized, manual workarounds proliferate, and maturity stalls — regardless of policy or governance intent. This isn’t a conversation about replacing a tool. It’s about recognizing a maturity inflection point — where the risk operating model itself needs to evolve, and technology must enable that shift rather than constrain it. These are the kinds of grounded, forward-looking discussions that lead to better GRC outcomes — and I’m seeing more organizations reach this point every month. _______________________ 🪐 As an industry analyst, I map and monitor the ever-expanding GRC galaxy — now tracking 1,500+ solutions and the professional services orbiting them . . . For those navigating this universe: 🔭 Reach out to GRC 20/20 Research, LLC for guidance on GRC solutions & strategy 📡 Follow GRC Report for ongoing insights and market trends 🎙️ Tune into my podcasts → Risk Is Our Business Podcast & Hitchhiker's Guide to the GRC Technology Galaxy Podcast

I just co-authored Part 1 of a three-part blog series on what is changing for financial institutions as innovation, including AI, moves from “future topic” to 𝘀𝘂𝗽𝗲𝗿𝘃𝗶𝘀𝗼𝗿𝘆 𝗿𝗲𝗮𝗹𝗶𝘁𝘆. For the last few years, many institutions have been waiting for clearer regulatory direction. Recently, the writing on the wall is harder to ignore. Recent FDIC commentary and testimony reinforce a simple point: 𝘢 𝘻𝘦𝘳𝘰-𝘳𝘪𝘴𝘬 𝘱𝘰𝘴𝘵𝘶𝘳𝘦 𝘵𝘰𝘸𝘢𝘳𝘥 𝘪𝘯𝘯𝘰𝘷𝘢𝘵𝘪𝘰𝘯 𝘪𝘴 𝘯𝘰𝘵 𝘵𝘩𝘦 𝘴𝘢𝘮𝘦 𝘢𝘴 𝘢 𝘴𝘢𝘧𝘦 𝘢𝘯𝘥 𝘴𝘰𝘶𝘯𝘥 𝘢𝘱𝘱𝘳𝘰𝘢𝘤𝘩. The signal is not “chase every new tool,” instead it is “move forward deliberately with a technology-neutral, risk-based approach and govern the risk well.” Sound familiar?? This approach has been there within our third-party risk management best practices, now it explicitly is calling out technology modernization buzzword like AI. In Part 1, my CLA (CliftonLarsonAllen) colleague Erica Crain and I outline where gaps tend to show up first:  • Vendor oversight that accounts for embedded AI and downstream third-party dependencies  • Risk management practices that address AI validation, monitoring, and accountability  • Cyber and information security controls for employee use of public generative AI tools  • Data readiness that is fit for purpose, not perfect  • Leadership and staff literacy so teams align on what they mean when they say “AI" If you are waiting for a single rulebook before you start, you may be waiting too long. Now is the time to build the foundation that lets your institution innovate responsibly. Read Part 1 here: https://lnkd.in/e49QNjbX Part 2 (AML and BSA use cases) and Part 3 (promising starting points across the institution) are coming soon! #CLADigital #ValueRiskServices #DigitalTransformation #StrategicPlanning #TechnologyModernization #RiskManagement #AI #VendorManagement #Cybersecurity #DataGovernance

Fast growth in the financial services industry presents a double-edged sword - it rewards you for tremendously challenging work, while posing significant compliance challenges. Just recently, we saw the CFPB ordered Navy Federal Credit Union to pay $95M for charging illegal overdraft fees. As of November 14, 2024, enforcement actions have resulted in $19.6 billion in consumer relief and $5 billion in civil money penalties for this year alone. As banks increase investments while expanding their operations, product offerings, and customer base, they often struggle to scale their compliance infrastructure at the same pace. This misalignment can lead to increased regulatory risks, fines, and reputational damage. Managing diverse risks across multiple jurisdictions further complicates compliance efforts. Add to this the need to balance innovation with compliance and growth, especially in areas like fintech and digital banking, and you realize it requires a delicate approach to avoid stifling growth while remaining compliant. Partnering with nimble vendors capable of swiftly adapting to regulatory changes isn’t just advantageous, it's a cornerstone of operational resilience in today's financial landscape.    

🚨 The UK wants to be a fintech superpower. So why did zero firms apply for a banking licence in 2025? After six applications in 2024, no firms applied for a UK banking licence in 2025. That came just as Revolut finally secured its full UK licence in March 2026, after a process that began in January 2021. This is probably a more worrying trend than one-off outlier. Revolut’s case proved two things at once: - The UK will approve large fintechs - The path can look long, painful and highly uncertain from the outside 🏛️ The regulator has a real problem too. The UK authorization process was built for banks that started small, local and simple. The Bank of England’s mobilization model still assumes a newly authorized bank will be in controlled build-out mode, with tightly restricted deposits while it finishes staffing, systems and operations. That is not what many fintech applicants look like now. Today, a firm may seek a license with: 👥 Millions of users ⚙️ Operations across multiple countries 💰 Billions in balances and transaction volume 💳 Lending, wealth, payments, subscriptions and crypto already live Assessing whether the compliance and risk function is good enough while it is being scaled in real time is much harder than assessing a small domestic start-up bank. Revolut’s licence delays were explicitly linked to concerns over whether its global risk controls were keeping pace with its international growth. 👇 Bottom line: The UK does not have an innovation problem. It may have a supervisory design problem. If the UK wants to be the best place to build the next generation of banks, it needs a regime that is both credible and faster at evaluating complex, globally scaled applicants. In banking some friction can be healthy, persistent friction becomes a deterrent. #Fintech #UKFintech #DigitalBanking #Regulation #FutureOfFinance

In the financial sector, compliance is king. Yes, AI can unlock enormous potential, better insights, streamlined processes, and even profit boosts. But if a shiny new model jeopardizes regulatory requirements, no bank will touch it. Period. This is the paradox of AI in finance: true innovation demands an almost extreme conservatism. Banks, operating under constant regulatory scrutiny, simply can’t afford to risk their licenses or reputations on solutions that don’t prioritize security and compliance from day one. The real path to AI adoption in finance isn’t about quick P&L wins; it’s about establishing trust and transparency. When we address regulatory barriers head-on, we set the stage for long-term success, because solutions that fully respect the rules are the only ones that will see the light of day in heavily regulated industries. Remember: a hypothetical 2% P&L boost means nothing if it comes with the threat of penalties or worse. By prioritizing governance, data privacy, and compliance upfront, we give AI the best chance to make a meaningful impact. Bottom line: If you’re building AI for finance, make regulation your top priority. That’s where true innovation meets practicality, and the only way forward in this industry.