Those results don’t come from technology alone. They come from digital transformation consulting that connects customer experience ambitions to the underlying engineering, data strategy, and AI capabilities required to deliver at scale. The banks that get this right won’t just compete with fintechs. They’ll set the terms of the next era of financial services.
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Open banking
Customer expectations didn’t wait for regulation to catch up. Across the UK, Brazil, and India, open banking already reshaped how people interact with their financial institutions, and the US is closing the gap fast. The CFPB’s long-anticipated rule on secure data sharing signals that American banks can’t treat open banking as a future-state conversation anymore.
But here’s the tension most banks aren’t talking about openly: the technical lift is real. Integrating with core and ancillary systems ranks as the top integration hurdle when banks partner with fintechs, and API security compounds the problem. Nearly a third of malicious requests target shadow APIs, unknown, unmanaged endpoints that accumulate quietly in complex enterprise environments. Addressing that risk isn’t optional; it’s foundational to any credible open banking platform strategy.
Where Brillio sees the opportunity is in positioning. Open banking doesn’t force banks into a single role. Some will compete as back-end service providers, leaning into compliance standards and infrastructure strength. Others will own the customer relationship through superior digital banking experiences and hyper-personalized financial services, pre-approved offers, tailored products, lifestyle-driven recommendations built on consented data. Both are viable paths. What isn’t viable is standing still.
For banks considering their open banking solutions roadmap, the architecture decisions made now will determine how quickly enterprise AI applications and digital transformation with AI can layer on top. Getting the API foundation right isn’t a technical formality. It’s a strategic bet on what the next era of banking looks like.
Banks challenges to meet digital banking expectations
The obstacles aren’t new, but the stakes have never been higher. Legacy systems built for a pre-mobile world can’t support the personalized, real-time experiences customers now expect as a baseline. And the pressure compounds fast: data privacy regulations tighten while API security vulnerabilities multiply, compliance demands evolve before the last update ships, and third-party integrations with budgeting apps or payment platforms introduce friction at every layer.
What makes this moment different is that the cost of inaction is now visible in market share, not just IT backlogs. Banks that have invested in enterprise AI solutions and modern digital platforms are demonstrably outpacing those still managing technical debt. The talent equation adds another layer of difficulty. Finding engineers who combine core banking knowledge with AI digital transformation fluency is genuinely hard, and closing that gap through reskilling takes time most transformation timelines don’t allow.
But here’s what the best-prepared institutions understand: these challenges don’t exist in isolation. A fragmented data architecture undermines customer experience design. Weak API governance creates compliance exposure. Talent shortfalls slow down the very digital transformation consulting work meant to fix everything else. The organizations pulling ahead treat this as a systems problem, not a checklist. They build digital banking capabilities that are architecturally sound, regulatory-ready, and designed around actual customer behavior rather than internal org charts. That integrated thinking is where the real separation happens.
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Green banking
Sustainability in banking isn’t a reputational exercise anymore. Increasingly, it’s a risk management discipline with measurable financial exposure at its core.
The Federal Reserve’s climate scenario analysis pilot asked six of the country’s largest banks to quantify how severe weather and warming trends could affect their residential and commercial real estate portfolios. That’s a direct signal: regulators now expect banks to treat climate risk the way they treat credit risk. Structured. Modeled. Reported.
The SEC’s forthcoming climate disclosure rule extends that logic beyond banking. About 70% of public companies plan to comply regardless of when it becomes final. For banks, that’s both a warning and an opening. Clients across sectors will need financing strategies tied to sustainable finance solutions, and the institutions best positioned to offer them will have already built the internal data infrastructure to track and report emissions exposure accurately.
On the opportunity side, green banking spans a wider surface than most lenders currently address. Mortgages tied to energy-efficient retrofits, lending programs that support renewable energy development, and B2B credit products aligned to low-carbon transition plans all represent viable, growing revenue pools. Enterprise AI solutions and AI-powered data platforms can help banks model portfolio-level climate risk, identify green lending opportunities, and generate the audit-ready reporting regulators increasingly expect.
The banks that treat sustainable banking as a digital transformation challenge, not just a compliance exercise, will be the ones that turn policy pressure into competitive differentiation.
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Core transformation
The buy-or-build question keeps bank executives up at night, and understandably so. Neobanks carry no legacy architecture, no technical debt, and cloud-native platforms that let them move at a pace traditional institutions simply can’t match on aging infrastructure. That structural gap is widening, not narrowing.
But the picture is more complicated than it first appears. Only about 5% of the roughly 500 neobanks operating today are actually profitable. Consolidation is already underway. That creates a genuine opening for established banks willing to make a disciplined call on their digital transformation path rather than chasing every fintech entrant.
For incumbents, two credible routes exist. The first is enterprise application modernization, stripping out legacy core systems and replacing them with cloud-native banking platforms that can support open banking, real-time payments, and AI-driven services. The second is a phased approach, modernizing specific layers, such as digital channels or payments processing, while managing the risk of full core replacement. Neither path is easy. Both demand rigorous digital transformation consulting to sequence investments correctly and avoid compounding existing technical debt.
What’s encouraging is that core banking solution providers are responding. Cloud-native versions of established systems are now shipping, which reduces one of the biggest barriers to enterprise AI solutions at the banking layer. JPMorgan Chase’s Chase UK operation, one million customers and $10 billion in deposits in year one, shows what’s possible when a core transformation strategy is executed with genuine conviction.
The window to act isn’t closing yet. But it is moving.
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Payment standardization
Think of ISO 20022 less as a technical upgrade and more as a shared language that the global payments industry has been negotiating for decades. Now it’s finally arriving. The standard is already live across SWIFT and the Asia-Pacific region, with the US rolling out on a staggered timeline that runs through 2025. That gap matters. Banks that treat this as a back-office IT migration will miss the bigger opportunity.
Richer data is the real prize. ISO 20022 messages carry structured, detailed information that legacy formats simply can’t hold, which translates directly into better anti-money laundering screening, fewer false positives, and faster cross-border transaction reconciliation. For enterprise banking and financial solutions teams, that’s not a compliance checkbox. It’s a foundation for payments modernization that compounds over time.
Proof of that compounding effect is already visible. After building a platform integration module purpose-built for processing ISO 20022 transaction and clearing messages, a leading financial services provider cut time to market by 32%. The architecture was designed to connect with multiple banks without delays and to scale alongside a long-term tech refresh roadmap, precisely the kind of innovative payment system thinking that separates prepared institutions from reactive ones.
But getting there requires honest assessment. Payment processing modernization at this scale touches core systems, middleware, and interoperability layers simultaneously. Banks that invest now in the right digital transformation with AI-informed engineering will be positioned to treat ISO 20022 not as a deadline to meet, but as infrastructure for the next decade of financial services innovation.
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Real-time payments
Card-based revenue has long been the economic backbone of retail banking. But FedNow’s arrival changes the calculus. Thirty-five early-adopter banks went live with the Federal Reserve’s instant payment service in July, and the pressure on laggards is building fast. Non-card-based transactions don’t carry the same interchange economics, and that’s precisely the monetization puzzle banks can’t solve by waiting.
The deeper challenge is infrastructure. Real-time payments demand cloud-based architecture, tight interoperability across systems, and middleware that won’t buckle under transaction volume. Banks that haven’t progressed their payments modernization journey are, bluntly, not ready. The gap between intent and execution is widest here.
Brillio’s approach treats FedNow integration not as a bolt-on but as a digital transformation with AI moment, one that forces banks to confront aging infrastructure head-on. Working with B2B solution provider Payment Components, our teams are helping institutions scope the true complexity of migration, from legacy core touchpoints to middleware integration requirements, before a single line of code changes. That scoping work is what separates a controlled transition from an expensive scramble. Banks that get the architecture right now will carry a structural advantage into every innovative payment system cycle that follows.
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AI-driven chatbot solutions
Thirty-seven percent of the US population interacted with a bank chatbot in 2022. That number understates the shift underway. The question for banks isn’t whether to deploy enterprise AI chatbot solutions, it’s how fast they can build the capability before customers stop asking twice.
Generative AI changes the calculus entirely. Earlier chatbot generations handled balance checks and branch hours. Today’s models, grounded in large language models and trained on financial data, can interpret complex portfolio scenarios, flag anomalies in spending patterns, and generate call summaries that reduce support costs without sacrificing accuracy. The leap from transactional to advisory is real, and it’s happening now in wealth management, retail banking, and beyond.
But capability alone isn’t the differentiator. Responsible deployment is. The CFPB’s 2023 chatbot report put financial institutions on notice: enterprise AI applications in customer-facing roles must be compliant, transparent, and capable of protecting consumer data. Banks that treat governance as an afterthought will face both regulatory and reputational exposure.
What Brillio sees in practice is that the most effective AI digital transformation in banking treats the chatbot layer as part of a broader agentic architecture, one where conversational agents connect to live data, escalation logic, and compliance guardrails simultaneously. That’s not a product feature. That’s an engineering commitment, and it’s where generative AI application development separates real enterprise readiness from a polished demo.
