Banking in 2026: Intelligence, Composability and Value Creation

by Amit Dua, SunTec Business Solutions

Banks are moving into 2026 with many of the same pressures that have shaped recent years: unpredictable markets, shifting customer expectations and cautious spending decisions. The pace of technology change has not slowed, but the way institutions evaluate that change is becoming more rigorous. Investments now need to show a clear connection to performance and long-term value, rather than innovation for its own sake. Many technology programs that once focused on scale or experimentation are now being reviewed through a more measured lens, centered on outcomes, resilience and responsible growth.

Connecting investment with outcomes

The last few years saw a rapid increase in AI pilots, proofs of concept and early deployments. As organizations look for measurable results, many are reassessing where AI is making a clear contribution and where expectations need to be reset. Only 15 per cent of AI leaders can currently link initiatives directly to profitability, and about a quarter of planned spending is expected to shift into 2027 while priorities are reviewed and business cases are strengthened.

This does not signal a slowdown in ambition. Global AI spending in banking is still expected to rise sharply. Instead, the emphasis is moving from isolated pilots to practical applications across core systems and business lines. The focus is shifting toward areas where AI can support better commercial decisions, enhance customer journeys and reduce friction in operational processes.

In this environment, AI is becoming more of an integrated capability than a standalone feature. Banks are beginning to connect data and decisioning across engagement, pricing, risk, servicing and revenue management. For example, intelligence can now support the entire deal lifecycle from auto-completing RFPs and suggesting product configurations to modeling pricing scenarios and assessing risk factors. When AI is embedded across these steps, institutions can deliver a more consistent and responsive client experience, while freeing up teams to focus on higher-value work. It also strengthens competitive positions by making decision-making faster and more informed.

Many banks are also revisiting how they measure AI performance. Beyond efficiency gains, there is growing interest in how AI contributes to margin improvement, customer lifetime value and more accurate risk evaluation. This broader measurement framework will become a defining part of AI strategy in 2026.

A more flexible architecture for banking

This shift in expectations is reinforcing the move away from tightly coupled, monolithic systems toward more composable models. Traditional architectures have often made change slow and costly, limiting the speed at which banks can update or launch new propositions especially in areas that touch multiple legacy systems.

By breaking applications into modular components, banks can update and deploy capabilities independently. This supports faster delivery and allows institutions to scale features without having to rework entire systems. It also improves resilience, as components can be adjusted, replaced or upgraded without disrupting the full technology stack.

Composable models also allow banks to assemble and adapt solutions as customer needs, market conditions or regulatory requirements evolve. This flexibility is becoming increasingly important as institutions navigate new reporting requirements, shifts in credit conditions and rising expectations around personalization.

As composable architectures mature and AI becomes more embedded, some banks are beginning to explore multi-agent environments capable of coordinating decisions and workflows across systems. While still early-stage, these environments have the potential to automate complex processes that span pricing, risk, compliance and operations, creating a more adaptive and data-driven banking ecosystem.

Low code and no code driving tech delivery change

The rise of low-code and no-code platforms is reshaping how solution providers build and deliver software for banks. Since most institutions rely on vendors for development and deployment, the onus is on providers to adopt LCNC approaches that accelerate delivery, simplify configuration, and reduce time-to-value. These platforms allow to roll out workflow changes, rule updates, integrations and enhancements rapidly without long development cycles or heavy engineering effort.

Generative AI adds further acceleration by supporting coding tasks, improving documentation and enabling teams to prototype solutions with far fewer manual inputs. These capabilities open up development to a broader range of contributors, giving banks more agility in delivering incremental improvements.

However, broader participation also heightens the need for strong governance. Version control, embedded compliance, audit trails, role-based access and clear boundaries around what can be automated will become essential in managing the risks associated with distributed development. The challenge for banks is to balance speed and empowerment with consistency, security and oversight.

For most institutions, the objective is not simply to move faster but to ensure that technology delivery remains aligned with business strategy, customer expectations and regulatory obligations.

2026 outlook

In 2026, AI adoption will be assessed more closely against ROI, operational impact and the institution’s broader transformation goals. LCNC and GenAI will continue to support development, but strong design principles, clarity of intent and customer-centered thinking remain fundamental. Banks that treat AI as a strategic capability rather than a collection of tools will see the greatest long-term benefit.

Technology alone will not deliver transformation. Continued investment in workforce skills, governance frameworks and organizational culture will be equally important, alongside strong cybersecurity and compliance capabilities. Institutions that combine modern architecture, intelligent automation and disciplined delivery will be in a stronger position to respond to change.

Success will increasingly be measured by the value created across the full banking ecosystem: for customers, employees, partners and regulators. Banks that prioritize transparency, measurable outcomes and consistent delivery will be best positioned to compete in the years ahead and to build technology foundations that support sustainable growth.