IBM data shows that, as of late 2024, only 8% of banks were developing generative AI in a truly strategic, enterprise-wide way, while 78% remained in “tactical mode.” ¹ But progress hasn’t been stalled by apathy but rather by complexity, as legacy tech stacks, fragmented data, and rigid compliance structures all slow momentum. Banks must also contend with cultural resistance, skill gaps, and the need for AI explainability to satisfy regulators and reassure customers. In short, it’s not hesitation holding them back, it’s the weight of responsibility.

That said, the tide seems to be turning in recent months. In fact, 82% of U.S. banks say they’ll increase the share of their overall budget devoted to AI, according to KPMG, and nearly four in ten expect AI to exceed 20% of total budget. ² This signals that the industry is finally leaning in, motivated by the promise of efficiency gains, scalability, and rising customer expectations for smarter, faster services.

Even the major consultancies are urging banks to act decisively in 2026. McKinsey & Company argues that to realize meaningful value from AI, banks must “move beyond experimentation to transform critical business areas,” highlighting multi-agent systems as key to re-engineering complex workflows. ³ And they’re not alone. The industry is clearly gearing up for scale, as The Financial Brand recently reported that Citi now requires 175,000 employees to complete AI training, a sign that the tech is about to touch every corner of that organization. ⁴

Together, these moves paint a clear picture: the AI revolution in banking is no longer hypothetical. It’s already here, and the institutions that move first and fastest will define the future of banking.

¹ IBM, Gen AI Will Elevate Financial Performance of Banks in 2025, February 2025.
² KPMG, Intelligent banking: a blueprint for creating value through AI-driven transformation, February 2025.
³ McKinsey & Company, Extracting value from AI in banking: rewiring the enterprise, December 2024.
⁴ The Financial Brand, We’re speeding past the tipping point of GenAI in banking, October 2025.

The Backbase view

2026 will be the year when AI moves from promise to performance in banking. While some still see the tech as an existential threat, others recognize it for what it truly is: a massive opportunity. And the banks that embed agentic assistance, workflow automation, and AI-driven compliance into their daily operations will start realizing measurable ROI, rather than just “productivity theater.”

The first wins are likely to appear in customer servicing, where AI can reduce resolution times and lower cost-to-serve. Compliance will follow, benefitting from automated reviews, stronger coverage, and enhanced explainability. Software delivery will also experience some of the most dramatic changes, with AI copilots and multi-agent orchestration reshaping the software development lifecycle (SDLC), end to end. In fact, in one McKinsey case study, a regional bank increased developer productivity by 40%, with over 80% of its engineers saying genAI improved the coding experience. ⁵ And that’s just one use case.

There’s no denying the hype around AI, both inside and outside of banking. But as Backbase CTO Adrian McPhee put it on the Banking Reinvented podcast, “something can be both hyped and genuinely transformational, they’re not mutually exclusive.” The difference between noise and impact will come down to mindset. The real winners in 2026 and beyond will view AI not as a toolbox, but as a catalyst for transformation, one that’s anchored in governed data, redesigned processes, and disciplined, risk-managed deployment at scale.

⁵ McKinsey & Company, Extracting value from AI in banking: rewiring the enterprise, December 2024.

Deloitte projects that genAI-enabled fraud losses could hit $40 billion by 2027 in the U.S. alone, up from $27 billion in 2023, a staggering increase that shows how fast this problem is growing. ⁶ And that figure only captures the financial fallout. But when customer trust in a bank is shaken, the reputational damage can ripple even further, eroding brand equity and long-term loyalty. The main culprits? Low-cost deepfakes, scalable impersonation, and automated social engineering that can target thousands of banking customers at once.

Deepfakes, in particular, are surging. Over the past three years, deepfake-related fraud attempts have increased by 2,137%, according to Signicat. ⁷ That means that more than 50% of detected fraud attempts now involve AI in some form, including everything from voice and video manipulation to injection attacks. ⁸ The message is clear: financial institutions must act fast to stem this rising tide before it overwhelms existing defences.

The problem is, many banks are scrambling to keep up, with only a third (36%) saying they’re even “somewhat confident” in their current fraud controls. ⁹ At the same time, synthetic identity fraud and deep-fake document scams are rapidly accelerating, and what was once niche is now being described as “the next systemic challenge” for financial services. ¹⁰

But there’s reason for optimism because AI can help us fight back, too. The industry is now turning to multi-layered defense strategies, using AI to power fraud orchestration that links detection systems across channels, and to strengthen behavioral biometrics and digital identity frameworks. According to Feedzai, 90% of financial institutions are now using AI to combat emerging fraud. ¹¹ But adoption still faces roadblocks: ethical concerns, explainability, and the sheer complexity of scaling new systems.

Time, however, is not on our side. As fraud becomes cheaper, faster, and more convincing, the window to get ahead of the threat is closing quickly. So the time to act is now.

⁶ Deloitte, Generative AI is expected to magnify the risk of deepfakes and other fraud in banking, May 2024.
⁷ Signicat, Fraud attempts with deepfakes have increased by 2,137% over the last three years, February 2025.
⁸ Feedzai, More than 50% of fraud involves the use of artificial intelligence, May 2025.
⁹ Equifax, The rising tide of fraud: a challenge for banks, February 2025.
¹⁰ FinTech Outlook, Synthetic identity fraud and deepfake document attacks: how banks can defend in 2025, September 2025.
¹¹ Feedzai, More than 50% of fraud involves the use of artificial intelligence, May 2025.

The Backbase view

As deepfakes and AI-generated scams spike across the financial sector, trust will emerge as the defining competitive edge of 2026. Customers will increasingly judge banks not just by how convenient they are, but how safe these institutions make them feel. The frontrunners will orchestrate proactively, unifying detection, decisioning, and case management across payments, onboarding, and servicing. Instead of just reacting to isolated alerts, they’ll use AI to identify patterns across systems and stop attacks before they spread.

The next step is continuous verification. By pairing behavioral biometrics with risk-based step-ups and stronger device and identity signals, banks can validate users seamlessly in the background, keeping genuine interactions frictionless while shutting out imposters. Alongside this, leading institutions will deploy content-authenticity controls such as liveness detection, deepfake analysis, and cryptographic watermarketing to guard against synthetic media.

Tech, though, isn’t enough. Trust must be visible to customers. Banks that explain how they protect their customers through anti-scam education, transparent fraud-resolution timelines, and clear accountability will earn lasting loyalty. In a world where AI has lowered the cost of deception, the winners will be those that operationalize trust, not just security, cutting losses and gaining market share across high-risk digital channels.

Instant payments are scaling rapidly, transforming how money moves for both individuals and businesses across the globe. They enable faster transactions, improved cash flow, enhanced security, and greater convenience, which is accelerating adoption worldwide. In the United States, two real-time systems are gaining traction: according to The Clearing House, Real-Time-Payments (RTP) surpassed one billion transactions by early 2025, while the FedNow network continues to onboard more banks every quarter. ¹² Meanwhile, Europe’s Instant Payments Regulation (IPR) now mandates that banks process euro transfers instantly, not just during business hours. Asia-Pacific and Latin America are also building momentum, with Brazil’s Pix network now reaching around 75% of the population, driving financial inclusion through free peer-to-peer transfers and low-cost merchant payments. ¹³ Together, these shifts make “instant” the new standard for both consumers and enterprises.

At the same time, digital wallets have become the primary payment interface. According to Capital One, digital wallet users topped 4.3 billion in 2024, representing 53% of the global population. ¹⁴ Apps like Apple Pay, Google Pay, Alipay, and Paytm are now everyday tools for millions, accounting for roughly 30% of global in-store spending and ranking among the top online payment methods, per McKinsey. ¹⁵ 

And digital money itself is getting smarter and more connected as governments test stablecoins and central-bank digital currencies (CBDCs). In the European Union, the Markets in Crypto-Assets Regulation (MiCA) framework sets clear rules for how stablecoins and digital euros must be issued and supervised. Projects like BIS’s mBridge and the European Central Bank’s digital-euro pilot are paving the way for cross-border, programmable payments, signaling that a new phase of global digital money is coming sooner, rather than later.

Here’s the bottom line: payments are blending into everything. Buying, borrowing, and paying are now built directly into the digital platforms people already use, from shopping apps to ride-hailing services and accounting tools. These transactions increasingly trigger instantly and invisibly in the background without disrupting the user experience, reshaping how banks earn revenue. Instead of relying on fees alone, financial institutions are starting to create value through services like risk management, data insights, and working-capital optimization. The stakes couldn’t be higher: payments remain the most profitable segment of financial services, generating $2.5 trillion in annual revenue from $2 quadrillion in value flows across 3.6 trillion transactions worldwide. ¹⁶ That’s why getting payments right isn’t optional, it’s foundational. And the digital leaders are already moving.

¹² The Clearing House, RTP® network doubles volume in 18 months, surpassing 1 billion transactions and driving U.S. payment innovation, February 2025.
¹³ Citi, Real-time: 24x7 finance in an always-on world, June 2025.
¹⁴ Capital One, Digital Wallet Statistics, July 2025.
¹⁵ McKinsey & Company, The 2025 McKinsey global payments report: competing systems, contested outcomes, September 2025.
¹⁶ McKinsey & Company, The 2025 McKinsey global payments report: competing systems, contested outcomes, September 2025.

The Backbase view

In 2026, payments will become fully embedded, invisible, and intelligent. Money movement will fully merge with everyday digital experiences. Whether a customer is paying a bill, sending funds abroad, or receiving their salary, the transaction will feel instant, automatic, and invisible. As McKinsey notes,“how money moves is becoming as critical as how much,” and the design choices being made today will determine who leads, who follows, and who falls behind over the next decade of payments. ¹⁷

For financial institutions, this moment represents a major opportunity. Banks and fintechs can now earn from orchestration, connecting cards, accounts, wallets, and digital currencies into a unified, seamless experience. With programmable, tokenized money, instant settlement, and unified APIs, institutions can launch new, value-added services at the moment of payment, from instant financing and foreign exchange (FX) optimization to data-driven insights and working-capital tools that strengthen client relationships while creating new revenue streams.

At the same time, these innovations will reshape what customers expect. Reliability, transparency, and interoperability across payment rails will become the new markers of trust. The banks that deliver smooth, always-on payment experiences, while embedding smart safeguards and insights in the background, will set the benchmark for modern money movement. In the race towards invisible payments, those who combine speed with intelligence will define the next era of growth in global finance.

¹⁷ McKinsey & Company, The 2025 McKinsey global payments report: competing systems, contested outcomes, September 2025.

But now, it’s evolving into something far more expansive: open finance and embedded ecosystems. Across Europe, PSD2 has already pushed banks to expose their APIs for account information and payment initiation, laying the groundwork for seamless data sharing and interoperability. And this trend shows no signs of slowing down. In fact, with 80% of banks worldwide planning to invest in open banking technology by 2025, Mastercard predicts that its use is expected to double by 2027 as markets continue to mature, innovate, and test concepts. ¹⁸

At the same time, the embedded finance and bank-as-a-service (BaaS) markets are surging. Embedded finance, valued at $104.8 billion in 2024, is projected to reach more than 834 billion by 2034, growing at roughly 23% annually, according to Global Market Insights. ¹⁹ BaaS, one of its primary enablers, is expected to follow a similar trajectory, expanding from tens of billions today to surpass 73 billion by 2034. ²⁰

Together, these models are redefining the role of the bank, from holding deposits and offering standalone products to providing platforms, data services, and embedded finance capabilities, partnering with even non-financial brands. By exposing their APIs, banks can now enable third-party innovation, turn data into a monetizable asset, and participate in ecosystems where financial services blend naturally into everyday experiences.

¹⁸ Mastercard, Open banking 2025 thoughts & trends, January 2025.
¹⁹ Global Market Insights, Embedded finance market size, January 2025
²⁰ Global Market Insights, Banking as a Service market size, May 2025.

The Backbase view

In 2026, banks will recognize that open banking wasn’t the destination: it was the launchpad. This former compliance requirement is now the engine for embedded distribution and ecosystem-led growth.

The leaders will be those that build scalable API platforms capable of monetizing access through ecosystem partnerships, embedded banking into non-bank apps, commerce platforms, and enterprise software. They’ll use data and analytics as active revenue streams, transforming account and transaction data into embedded credit, risk-scoring, and tailored financial services.

Winning institutions will also embrace embedded finance, bringing financial services to where customers already are, rather than expecting them to come to the bank. Crucially, they’ll treat regulatory infrastructure as a competitive advantage, not a burden. The next frontier? Business orchestration, where compliance, tech, and data strategy converge to unlock new growth engines, broader reach, and lasting relevance in customers’ digital lives.

In fact, the global neobanking market was valued at $210 billion in 2025 and is projected to grow by 48.9% compound annual growth rate (CAGR), reaching $3.4 trillion by 2032. ²¹ This explosive growth is putting incumbent banks under real pressure, especially those still struggling to harness the power of AI. According to Boston Consulting Group (BCG), only one in four banks worldwide is actively using AI to gain a competitive advantage. ²² The rest remain stuck in fragmented pilots and proofs of concept, risking irrelevance as digital-first competitors race ahead.

Because of this AI adoption gap, combined with tech, scale, and data advantages, neobanks and tech titans are moving faster, delivering sharper experiences, and challenging incumbents across pricing, speed, and user experiences. And their platform business models let them learn from every interaction and iterate in real time.

As BCG puts it, “predictive, generative, and agentic AI are redefining the foundations of scale, efficiency, and customer experience.” ²³ Neobanks have realized this, and they’ve taken action. Unfortunately, incumbent banks aren’t nearly as agile, making adoption a real headache. But banks that fail to adapt risk becoming utilities in a market where customers expect immediacy, personalization, and constant innovation.

²¹ Fortune Business Insights, Neobanking market size, share & industry analysis, 2025 – 2032, October 2025.
²² Boston Consulting Group, For banks, the AI reckoning is here, May 2025.
²³ Boston Consulting Group, For banks, the AI reckoning is here, May 2025.

The Backbase view

In 2026, incumbent banks will face their toughest competitive test yet. The race will come down to speed, scale, and experience, with AI as the engine. Neobanks continue to scale globally on lightweight, cloud-native infrastructures, while tech giants are embedding financial services into lifestyle ecosystems, with payments, credit, and savings woven seamlessly into everyday life. Customers now expect their bank to be as personalized as Netflix, as easy as Amazon, and as intuitive as their favorite social media app.

The stakes are high, but incumbents can still win. To compete, they need to build unified, AI-powered platforms that connect data, analytics, and channels, end to end. That means using AI to automate intelligently, cutting costs while personalizing each and every interaction. That requires a platform mindset, including open APIs, deep partnerships, and embedded services, instead of defending legacy silos. And the differentiator won't just be efficiency, it will be experience: predictive servicing, adaptive interfaces, and contextual offers that feel proactive, rather than reactive.

Banks that act decisively in 2026 will not only survive, they’ll thrive. By aligning around a unified platform strategy and deploying AI where it drives value, incumbents can meet the pace set by neobanks and tech titans. The opportunity is within reach, but the time to move is now.

Everyday banking activities, from checking balances to paying bills and transferring money, have become seamless as AI systems take over. In fact, 85% of banking executives believe AI will significantly transform the industry within five years, seeing it as critical to their competitiveness. ²⁴ And with global retail-banking revenue standing now at $3.6 trillion, future growth will depend on how well banks integrate digital intelligence into their customer experiences. ²⁵

This transformation is giving rise to invisible banking, where AI acts as a financial co-pilot for retail customers. Advanced algorithms and conversational agents are now able to automate savings, bill payments, and even real-time, personalized advice, quietly optimizing financial outcomes in the background. For example, Bank of America’s virtual assistant, Erica, has surpassed 2.5 billion client interactions, handling requests and providing proactive insights for 20 million customers. ²⁶ It’s become the new norm to anticipate customer behavior and demands, rather than responding to it, offering value before they even know what they need. And this should be possible for even the smallest customer, according to Accenture, as generative AI enables banks to efficiently tailor offerings, at scale. ²⁷ But this AI-driven intelligence is only as powerful as the infrastructure beneath it. Banks will need modern payment rails and interoperable systems capable of executing those intelligent systems instantly.

That’s why the evolution of AI in retail banking is inseparable from the modernization of payments. Digital wallets and instant-payment rails continue to grow in importance in everyday transactions, putting immense pressure on banks’ traditional revenue streams and pushing them to modernize their legacy infrastructures. And this will only accelerate. In fact, Capgemini predicts that instant payment volumes will grow from roughly 16% in 2023 to 22% by 2028, while wallets and agent-to-agent (A2A) payments gain traction. ²⁸ In this context, payments are becoming the connective tissue that allows AI-driven insights to translate into real-world actions, whether that’s automating bills, reallocating savings, or funding investments in real time. As digital money becomes programmable, with central-bank digital-currency pilots and stablecoin frameworks like MiCA, customers are quickly growing accustomed to seamless, always-on payment flows.

As AI assistants evolve, their real promise lies in advancing financial wellbeing. By turning banks into personalized guidance, nudging customers towards better spending, saving, and investing decisions, AI can help people make smarter financial choices in real time. This marks a deeper shift: banks are no longer just service providers, but active partners in their customers’ financial lives, empowering them to build resilience and security through education and proactive advice. As Deloitte notes, retail banking is at a crossroads, and financial institutions that thrive will be those that embed considerations of wellbeing into every interaction, making customer-centricity not a goal, but the foundation of their operating model. ²⁹

²⁴ Gitnux, AI in the banking industry statistics, April 2025.
²⁵ Research and Markets, Retail banking market report 2025, September 2025.
²⁶ Bank of America, Digital Interactions by BofA Clients Surge to Over 26 Billion, up 12% Year-Over-Year, February 2025.
²⁷ Accenture, Banking: the future is back, trends shaping the industry in 2025 and beyond, 2025.
²⁸ Capgemini, World Retail Banking Report: attract, engage, and delight,” 2025.
²⁹ Deloitte, The future of retail banking: ten moves to help you turn uncertainty into advantage, June 2025.

The Backbase view

In 2026, retail banking will become significantly more personal, predictive, and invisible. AI will sit at the heart of each customer interaction, anticipating needs, performing repetitive tasks, managing money in the background, and embedding financial decisions in daily routines. That will allow banks to give customers what they want, when they want it, at scale.

The winners will be the ones who can pull off AI-driven orchestration, unifying data, personalization, and payments across every channel. Agentic assistants will automate things like savings and cash-flow decisions, while predictive insights will help customers make smarter choices before they even realize the need. But that means banks will need to extend their value props beyond convenience to offer financial-wellbeing coaching as a core differentiator, providing full transparency and inspiring trust.

Those that adapt quickly will see new loyalty and revenue streams emerge through proactive, data-driven experiences. And those that hesitate? They risk being relegated to the background, visible only when something goes wrong in the financial lives of their customers.

In fact, some banks are already using 100+ AI and machine-learning algorithms, analyzing 15,000 customer data points to generate various types of nudges, such as personalized product recommendations and milestone celebrations. ³⁰ This enables a deeper, wider reach for relationship managers, empowering “segment-of-one” personalization and seamless, omnichannel engagement.

Data orchestration and unified ecosystems are the key enablers here, while trust and transparency are rising in importance. In fact, according to EY, the transformation of private banking now hinges on finding ways to combine human expertise with data-driven advisory, and firms must act now to define how advisory conversations can become more strategic, data-driven, and trust-based, rather than purely transactional. ³¹

These hybrid advisory models, where human advisors and digital assistants collaborate, are swiftly becoming the baseline, rather than the exception. And AI isn’t just helping firms serve more clients, it’s helping them serve every client better. Intelligent copilots allow banks to elevate the minimum standard of service across their entire client book, ensuring that even lower-value segments receive consistent, proactive, high-quality engagement. The result? A higher floor for service excellence and a stronger foundation for retention and long-term loyalty.

³⁰ Acuity Knowledge Partners, AI in private banking: hyper-personalization and democratization of advisory services, May 2025.
³¹ EY, How to leverage AI for growth and cost efficiency in private banking, April 2025.

The Backbase view

In 2026, private banking will be defined by augmented relationships and intelligent advisory. To get ahead and stay ahead, firms must elevate their relationship managers into the role of orchestrators, enabled by AI agents, data-rich insights, and seamless, multi-channel engagements.

Agentic advisors will multiply reach, with copilots preparing portfolios, surfacing next-best actions, summarizing research, and freeing advisors up to focus on higher-value strategic conversations, rather than administrative tasks. Data orchestration will fuel true one-to-one advice, while unified wealth, transaction, and behavioral data will drive recommendations that anticipate life-stage transitions, investment themes, and risk posture.

And as with retail, trust and transparency will define value. Clients are already demanding that the use of AI and data is explainable, governed, and anchored in personalized guardrails, not black boxes. Private banks that master the fusion of human expertise plus digital precision will carve out the next generation of client loyalty and growth.

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AI’s influence is becoming significant, with one report suggesting that nearly 42% of wealth management work could be redefined by this tech by 2030. ³² Meanwhile, McKinsey notes that AI could boost software engineering productivity by 20-45%, which serves as a useful proxy for the back-end uplift that wealth-tech systems could achieve. ³³

Advisors are beginning to transition from purely human-driven models to hybrid advisory systems, where human expertise is augmented by digital tools, data orchestration, and the automation of routine tasks like documentation. As AI capabilities are further embedded into wealth platforms and advisor workflows, the promise is faster, smarter, more personalized client experiences.

Finally, values-based investing, digital onboarding, and continuous portfolio optimization are moving closer to the mainstream. The ingredients are all there: unified data ecosystems, agent-based advisory, frictionless verification for affluent clients, and the automation of tasks once viewed as “too bespoke” for scale. All of this progress, however, must preserve the hallmark of wealth management: delivering high-touch, white-glove service through relationship managers who remain firmly at the center of the client experience.

³² Business Insider Africa, Almost half of the work banks do could be ‘redefined’ by 2030. Here’s a breakdown, July 2025.
³³ McKinsey & Company, The economic potential of generative AI: the next productivity frontier, June 2023.

The Backbase view

In 2026, wealth management will be defined by two simultaneous forces: hyper-automation in operations and deep personalization in client experiences. Agentic advisors, which are already becoming increasingly popular, will be the new norm. AI copilots can handle the heavy lifting, including prep work, portfolio reviews, and next-best-action suggestions, freeing human advisors up to focus on high-value conversations around life goals, values, and complex strategy.

Thanks to advancements in large language models (LLMs), firms will now be able to deliver truly personal engagement at scale, serving far more clients, and far more efficiently than ever before. Where once it was uneconomical to offer high-touch service to all but the wealthiest clients, AI now makes it viable to extend personalized planning, insights, and guidance to the broader mass affluent segment. This means wealth managers can widen their reach while maintaining quality and depth of service, opening entirely new growth audiences.

At the same time, onboarding and access will scale without losing exclusivity. With digital know your customer (KYC), seamless verification, and friction-free onboarding flows, wealth firms will be able to serve HNWIs and ultra-high-net-worth individuals (UHNWIs) with greater efficiency and reach. And finally, values-based and thematic investing will no longer be niche, but rather expected. Clients will increasingly ask for portfolios that are aligned with their environmental, social, and governance (ESG) and impact themes, meaning wealth firms will need to embed these into their platform capabilities to differentiate.

The message for wealth firms is clear: it’s time to move from pilot-to-scale, from product-led to experience-led. To win in 2026, firms will need to build the unified data, agent-enabled workflows, and transparent advisory models that will define the next decade of wealth management.

Digital onboarding and embedded-finance models are gaining traction, with banks increasingly offering lean document workflows, API-driven credit, and embedded finance tools via non-bank platforms, according to Global Banking & Finance Review. ³⁴ This model is critical: embedded finance is experiencing rapid growth, now accounting for an estimated total addressable market (TAM) of $185 billion in the U.S. and Europe alone. ³⁵

In parallel, banks are adopting AI and alternative-data scoring models to handle SMBs with thin files or informal financial histories. New machine-learning models have vastly improved accuracy in SMB credit risk categorization compared to older methods, allowing banks to minimize their losses and scale quickly. At the same time, digital-onboarding platforms are enabling faster time-to-disbursement.

Banks are also shifting from product delivery to orchestration of a richer ecosystem of services for SMB clients. From embedded payments and logistics tools inside accounting or supply-chain platforms to dynamic credit models that adjust with business performance, the new model is about context-aware service, rather than one-size-fits-all. And this is becoming essential, as a recent McKinsey piece notes that for micro, small, and medium enterprises (MSMEs), an excellent digital experience is now the top reason for choosing a primary bank. ³⁶ The stakes are high, and a lot of banks will need to play catch-up if they want to stay in the race.

³⁴ Global Banking & Finance Review, The digital banking era for SMEs: trends, innovations, and opportunities, January 2025.
³⁵ Boston Consulting Group, Moving embedded finance from promise to practice, September 2025.
³⁶ McKinsey & Company, Digital-led with a human touch: the next era in small-business banking, August 2025.

The Backbase view

In 2026, SMB banking will be redefined, with speed, precision, and ecosystems-based intelligence as the baseline. Banks that win will be the ones that overhaul their systems and become true enablers of small business growth. That means understanding the very different needs across the SMB spectrum, from small proprietors and microenterprises to mid-sized firms with more complex payments and trade demands.

For one thing, they’ll deploy agentic-digital collaboration, where bankers are supported by AI copilots that monitor cash reserves, flag risks, and suggest next steps proactively. For smaller businesses, this might mean AI-driven nudges around cash flow discipline or invoice management, while medium-sized enterprises could benefit from predictive insights into working capital and supply-chain exposure. These institutions will streamline onboarding via almost-instantaneous KYC and credit decisions, with digital workflows and embedded finance elements built directly into the platforms SMBs already use: accounting tools, logistics portals, and marketplaces. Embedded services such as payments, insurance, and working-capital credit will no longer be peripheral: they’ll be at the core of the SMB banking proposition.

To stay relevant, banks must leverage:

• Modular architecture: using plug-in models, open APIs, and fintech partnerships as table stakes for interoperability.
• Dynamic credit models: implementing models that adjust pricing and limits in real time, based on operational data, ownership changes, and supply-chain signals.
• Segment-sensitive models: recognizing that what works for a freelancer or family-run business won’t fit a regional manufacturer with a formal credit history.
• Alternative data scoring: supporting informal SMBs and thin-file clients to expand the addressable market.
• AI governance: building trust through transparent models, clear guardrails, and human oversight of all AI-driven decisions.

The financial institutions that will pull this off won’t just serve SMBs, they’ll become integral to their growth journeys going forward.

According to Datos Insights, commercial banking is shifting from defensive to offensive strategies, where real-time payments, API-first infrastructure and agentic AI are becoming the price of admission. ³⁷

In particular, banks and businesses are exploring API-led treasury and balance-sheet orchestration, with real-time APIs, modular treasury services, and AI forecasting enabling joint optimization of liquidity, payments, FX risk, and working capital. Across the industry, treasury leaders are no longer focused merely on speed or security. They’re re-architecting payment infrastructure to achieve total visibility and control, embedding finance APIs that connect treasury directly to core operations and unlock real-time decisioning across the enterprise.

Operations and credit functions are also being transformed. Commercial banks are increasingly deploying AI-centric risk, credit, and portfolio-management frameworks, including predictive analytics for real-time scoring and continuous monitoring. Data indicates that 70% of commercial banks have adopted AI in at least one core banking function, and 78% of banks investing in AI have seen a positive ROI within 18 months. ³⁸

Finally, banking architectures are evolving from monolithic legacy systems to composable, cloud-native cores and open architectures with modular plug-ins and fintech partnerships. This ecosystem shift also emphasizes sustainability and ESG, with embedding lending, carbon-tracking products, and green asset factors becoming standard features, rather than niche offerings.

³⁷ Datos Insights, Top trends in commercial banking & payments, 2025: switching from defense to offense, January 2025.
³⁸ WifiTalents, AI in the commercial banking industry statistics, June 2025.
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The Backbase view

In 2026, commercial banking will become predictive, modular, and growth-driven. The leading banks will be those that re-architect themselves for speed, adaptability, and value delivery, rather than simply risk mitigation. While commercial banking will continue to focus on large, complex enterprises with global footprints and multi-currency needs, it will also need to prioritize mid-market firms, those growing fast enough to need sophistication but still seeking agility and partnership, rather than scale alone.

First, banks will need to lead with API-first treasury and balance-sheet orchestration. They’ll offer modular treasury services and real-time APIs that allow corporations to optimize cash, payments, FX, and working capital in one integrated flow. These banks won’t simply be “banks of record,” but banks of orchestration, enabling their clients to move effortlessly across functions and respond in real time to market and operational shifts.

Second, agentic operations and AI-centric risk will become the norm, including:

• Intelligent workflows: autonomous agents will coordinate everything from onboarding and compliance to reconciliation and audit. This means empowering relationship managers, freeing them from administrative workloads so they can focus on advisory and client growth. This translates to less friction, faster cycle times, fewer exceptions, and an operational backbone capable of scaling intelligently.
• Predictive risk: alongside that, commercial banks will deploy AI-driven credit and portfolio management, using predictive analytics to monitor exposures in real time, re-price dynamically, and serve clients previously underserved by the classic paradigm.

Thirdly, innovation in business models and architecture will dominate the segment, including:

• Sustainability as revenue: ESG will no longer be an optional add-on, but a growth engine, with banks embedding green asset factories, ESG-linked lending, and carbon-tracking into standard commercial offerings.
• Ecosystem architecture: embedded finance ecosystems will become mainstream, and banks will provide plug-in models via open architecture to third-party ecosystems, extending their reach and relevance.

In short, 2026 will demand that commercial banks act less like monolithic institutions and more like modular platforms, unlocking growth through intelligence, interoperability, and purpose.