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The era of unchecked digital experimentation in retail banking is transitioning into a period of disciplined execution. According to KPMG’s 2026 Banking Industry Technology Survey, which gathered insights from 200 banking executives, financial institutions are sharpening their investment focus. Instead of spreading capital across every emerging trend, banks are concentrating resources on a select group of high-impact initiatives designed to optimize current operations and build long-term competitive resilience.
Key Insight: Future market differentiation will not come from adopting every new technology on the market. Instead, it will belong to institutions that master foundational technologies—specifically those that improve customer experience, strengthen operational resilience, and increase organizational agility.
Quick Insights: What Banking Leaders Need to Know
- Data Quality is a Universal Challenge: 100% of survey respondents identified data quality as a major hurdle in their data modernization efforts.
- M&A is Driven by Tech Needs: 67% of executives stated that acquiring advanced AI, analytics, or data capabilities is a primary objective when evaluating potential merger and acquisition targets.
- AI is Moving Into Production: 76% of financial institutions are already using or piloting generative AI to drive data personalization and internal business insights.
- Payments Modernization is Accelerating: 72% of banks are actively modernizing their platforms to support FedNow instant payments, while 70% are investing heavily in Real-Time Payments (RTP) infrastructure.
- Optimizing Existing Customer Channels: While digital customer experience remains a top priority, banks are focusing on refining and upgrading their existing mobile and online banking channels rather than building entirely new customer interfaces.
Laser-Focused Budgets Replace Broad Tech Spending
For years, financial institutions pursued broad digital transformation strategies across nearly every business unit. Today, macroeconomic pressures and practical realities have forced a strategic pivot. Spending is now concentrated on a few vital areas: cybersecurity, artificial intelligence, data modernization, payments, and customer experience.
In the coming year, operational efficiency and automated workflows rank as the highest investment priorities, followed closely by robust fraud prevention and security protocols. Rather than launching experimental new platforms, banks are choosing to improve the platforms they already have. Online and mobile banking upgrades remain universal priorities, with generative AI tools, chatbots, and virtual assistants transitioning from experimental novelties into mainstream customer-facing tools.
This tech-first mindset is also reshaping corporate development strategies. More than 75% of respondents indicated that technology capabilities significantly influence or directly drive their acquisition decisions. Financial institutions are increasingly looking to acquire smaller companies not just for market share, but to absorb specialized AI talent, data analytics infrastructure, and cyber defense capabilities.
The Core Challenge: AI Innovation Demands Better Data
Artificial intelligence has successfully transitioned from a theoretical future capability to an everyday operational necessity. More banks now view generative AI as a near-term strategic priority. Currently, the primary focus for AI deployment centers on boosting internal productivity, optimizing operational workflows, and elevating customer support systems.
However, the enthusiasm surrounding enterprise AI is meeting a harsh reality: legacy systems and poor data management. The KPMG survey revealed that insufficient governance frameworks, legacy technology integration, and difficulty measuring return on investment (ROI) are key obstacles to AI deployment.
Above all, poor data quality remains the single greatest barrier. Over half of the executives surveyed cited data readiness as the primary challenge in deploying enterprise AI. Furthermore, every single respondent noted that data quality issues continue to plague their broader modernization efforts.
For AI to deliver on its promise, banks must shift their data strategies. This means moving beyond simple regulatory compliance and focusing on building clean, accessible, and well-governed data ecosystems that can power hyper-personalized customer experiences and automated decision-making.
Defensive Security, Instant Payments, and Future Preparedness
As cyber threats grow increasingly sophisticated—with bad actors leveraging AI to launch attacks—banks are fighting fire with fire. Approximately 90% of financial institutions are now piloting or deploying generative AI specifically for fraud detection and threat mitigation.
At the same time, banks are taking a closer look at technology concentration risks. Nearly 70% of executives identified their heavy reliance on major cloud providers as a significant risk factor, followed closely by third-party vendor dependencies.
In the payments space, modernized infrastructure is no longer optional. While institutions continue to maintain traditional ACH and wire platforms, the primary focus has shifted to real-time transactional networks. Investment in FedNow and RTP integration is outstripping legacy payment upgrades, driven by a market-wide demand for instant settlement capabilities.
Looking further ahead, tier-one institutions are already designing systems capable of supporting next-generation transaction models. While still in the evaluation phase for many regional players, larger banks are proactively building infrastructure to support tokenized deposits and stablecoins, ensuring they are prepared for the future of digital asset management.
The Bottom Line: Winning banks are entering an execution-oriented phase of technology deployment. Success will not be defined by the sheer volume of technologies adopted, but by how effectively an institution integrates these tools into a unified, secure, and data-driven operational strategy.
Source: thefinancialbrand.com