EY Survey Finds Banks Investing in AI & Data Infrastructure to Overhaul Regulatory Reporting

Key Takeaways

• AI Adoption Plans Are Widespread: EY found that 87% of surveyed banking institutions plan to leverage AI-powered tools within the next one to three years, with half expecting to develop capabilities internally rather than rely on third-party products.
• Data Infrastructure Leads Technology Priorities: Authorized data stores were selected as a technology enhancement priority by 68% of respondents, reflecting investment in more reliable data sources, reporting infrastructure and automation.
• Governance Committees Are Well Established: Nearly all participating institutions reported having regulatory reporting governance committees, with 91% assigning them responsibility for issue management and escalation.
• Reporting Teams Are Being Reorganized: Hybrid production structures accounted for 54% of respondents, while 46% used report-based models. EY also identified expanding teams, alternative delivery arrangements and increasing offshore support.
• Operating Model Transformation Remains a Priority: EY expects banks to continue integrating changes in governance, data, technology and workforce capabilities as they respond to evolving regulatory requirements and supervisory expectations.

Deep Dive

Banks are preparing to bring artificial intelligence into regulatory reporting on a considerable scale, even as they continue investing in the data systems and internal controls needed to make the technology useful.

A new survey from EY found that 87% of participating banking institutions plan to use AI-powered tools within the next one to three years, with half expecting to develop those capabilities internally. The findings point to a broader reconsideration of how banks produce regulatory information, oversee its accuracy and organize the teams responsible for submitting it.

Published October 16, the 2026 EY Regulatory Reporting Target Operating Model Survey included all eight US-based global systemically important banks, alongside large and foreign banking organizations, regional banks and US branches of foreign banks.

The research, led by EY regulatory reporting specialists Vadim Tovshteyn and Christine Burke, follows the firm's previous survey in 2023. EY found that institutions have become more deliberate in their modernization efforts, increasingly treating improvements to data architecture, automation and governance as parts of the same undertaking.

The emphasis on AI is particularly pronounced, although the survey's findings concern planned adoption rather than completed deployments. Banks are exploring applications across regulatory interpretation, data analysis, report production and review, with the aim of reducing manual work and allowing employees to devote more attention to investigating problems and assessing reporting quality.

The decision by half of respondents to pursue internal development suggests that many institutions expect AI to become closely integrated with their existing reporting systems. Regulatory submissions draw on information collected across different business activities, often through processes designed for purposes other than regulatory reporting. Introducing AI into that environment requires institutions to consider how the technology will interact with established controls and the data on which those controls depend.

EY's findings also show that banks are directing substantial investment toward the infrastructure beneath their reporting operations. Authorized data stores were the most frequently selected technology enhancement category, identified by 68% of surveyed institutions. Banks are prioritizing more dependable sources of information, improvements in data quality and greater automation across the reporting process.

Those investments address a persistent difficulty in regulatory reporting. Information used in a submission may originate in several systems and pass through multiple stages of processing before reaching the team responsible for the final report. Establishing its accuracy requires more than checking the finished figures. Institutions must also understand where the information came from, how it was changed and whether problems were identified along the way.

EY describes a movement toward data-first architectures intended to improve consistency and support reporting operations as requirements become more complex. Such investments are also important to banks' AI plans. Tools designed to analyze or produce regulatory information remain dependent on the reliability of the data they receive.

The survey does not quantify improvements in accuracy or efficiency resulting from these investments. It does, however, establish that banks are giving the underlying information infrastructure considerable attention rather than concentrating exclusively on new reporting applications.

Governance is receiving similar scrutiny. Nearly all surveyed institutions reported having a regulatory reporting governance committee, while 91% identified issue management and escalation as responsibilities of those committees.

The figures suggest that formal oversight is firmly established among the participating banks. They also reflect the importance of determining how reporting problems are handled once discovered, particularly when their causes lie outside the department responsible for preparing a submission.

A reporting discrepancy may originate in a business unit, a data management process or a technology system. Resolving it can require decisions involving several parts of the institution. Governance committees provide a structure for overseeing those issues, although their existence alone cannot establish whether problems are being resolved effectively.

EY identifies clearer accountability, stronger controls and more consistent issue management as priorities for institutions seeking to improve their reporting operations. These arrangements will become increasingly relevant as banks introduce technologies that can perform more of the work previously handled by employees.

The changes are also affecting how reporting teams are organized. The survey found that 54% of participating institutions use hybrid production team structures, compared with 46% operating through report-based models. Those approaches predominated across different types of banks, suggesting considerable consistency in the organization of reporting production.

EY also reported that institutions are expanding their reporting teams, making greater use of alternative delivery arrangements and increasing offshore support. Banks are reconsidering where work should be performed and how responsibilities should be distributed as they invest across the data supply chain.

The findings do not identify a single organizational structure as preferable. Rather, they show institutions adjusting their staffing and delivery arrangements alongside changes to reporting systems and processes.

The workforce implications are likely to become more pronounced as AI adoption progresses. Automation may reduce the amount of time spent preparing and checking information manually, while increasing the importance of employees who can assess exceptions, understand reporting requirements and exercise judgment over the resulting submissions.

EY expects operating model transformation, including AI implementation, to remain a defining theme for regulatory reporting functions over the next several years. The firm's assessment is that institutions will need to coordinate changes in technology, processes and workforce capabilities while responding to changing supervisory expectations and economic conditions.

The longer-term ambition extends beyond producing regulatory submissions more efficiently. EY argues that stronger data foundations and better-integrated reporting functions could also improve the information available for business decisions, giving regulatory reporting a more substantial role within financial institutions.

Whether banks can achieve that ambition remains an open question. The survey establishes where institutions intend to invest and how they are organizing their efforts, but it does not demonstrate that these changes have already produced more reliable submissions or better business outcomes.

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