A clear divide is emerging in the banking sector. Leading institutions are treating decision-making capability as a strategic priority, underpinned by sustained investment in technology and data improvement. This means using all available data, ensuring it is consistent, well-governed, and applied across the functions involved in decision-making.
As outlined in recent Moody’s research, The intelligence edge: Banking’s new decision advantage, leading banks recognize that trusted data foundations are required to scale AI analytics and capabilities across the enterprise, rather than limiting them to individual workflows that have historically operated in silos.
Building trusted data foundations
Banks increasingly recognize that data quality and connectivity are not back-office infrastructure concerns, but front-line strategic priorities. Data modernization is being treated as a prerequisite for improved customer engagement, enabling faster credit decisions, stronger risk assessment, and more accurate regulatory compliance.
Progressive large global banks, as well as mid-sized regional and national institutions, are taking a distinctly holistic approach. Rather than deploying isolated point solutions that address symptoms without resolving underlying connectivity issues, they are investing in enterprise-wide data governance and infrastructure. This ensures that data, as well as the decisions derived from it, are transparent and traceable across functions.
Leading banks are also building cultural capability. Forward-looking institutions are actively managing resistance from what one executive described as “legacy teams”—functions whose established ways of working are incompatible with the integrated, data-driven environments leadership is seeking to create.
A key differentiator is the stage at which risk is embedded in the process. Leading banks integrate risk insights at origination rather than introducing them later as a checkpoint. When risk is upstream, commercial teams can move with greater confidence. When it is downstream, decision-making is more likely to slow.
Scaling AI with governance built in
Another defining characteristic of effective AI integration in regulated organizations is robust AI governance infrastructure. This includes frameworks that enable AI deployment at scale while maintaining explainability and traceability.
According to the research, leading institutions are investing in AI across data analytics and insights (50%), workflow integration (48%), and data structuring (40%). Importantly, these investments are coordinated, allowing their individual value to compound.
Smaller banks are more likely than large global institutions to prioritize AI for data analytics and insights (+6%) and technology that improves workflow integration (+7%). Banks in the EU and UK are also more likely to invest in technology-driven insights (+8%) compared with peers in other regions.
Embracing the agentic AI frontier
Agentic AI adoption is now widespread. Nearly four in five banks report using it either broadly across most teams (36%) or selectively within specific functions (43%). Adoption is particularly advanced among large global banks, where close to 90% report active usage.
Banks are deploying AI systems to automate recommendations, route decisions, and trigger workflows within defined governance parameters. Current AI deployment is strongest in data, analytics, and technology (45%), compliance and financial crime (35%), and finance and treasury (30%).
Looking ahead two to three years, bankers expect the greatest AI impact in data, analytics, and technology (68%), compliance and financial crime (61%), and credit risk (53%). These are areas where slower decision-making can materially affect profitability. Governance remains the critical enabler: agentic AI scales in regulated environments only when explainability and traceability are designed in from the outset.
Integrating intelligence across workflows
One of the most powerful characteristics of leading banks’ strategies is their commitment to workflow integration. By ensuring insights are consistent across functions, banks reduce the uncertainty that arises when teams operate from fragmented or contradictory data.
This shift is strengthening risk and compliance accountability. Fraud and financial crime are a top focus area for 51% of banks, while 40% are prioritizing cross-functional risk integration across risk, finance, and lending. Leading institutions are deploying AI to decode complex transaction patterns in near real time, dramatically reducing investigation timelines that previously required hours of manual analysis.
The commercial dividend
Faster time-to-decision is increasingly translating into competitive advantage. More accurate risk assessment enables more precise pricing, while integrated compliance reduces the operational drag of regulatory complexity. At the same time, more personalized customer engagement, which is enabled by a unified data view, is improving retention and deepening client relationships.
Join Andrew Bockelman, Head of Banking at Moody’s, and James Partridge, Head of Industry Practice Leads, Americas, on June 2 at 9:00 a.m. ET to explore findings from Moody’s 2026 research and hear directly from industry leaders on what will set the next generation of leading banks apart.