Regnology Report Reveals AI's Potential in Regulatory Reporting Efficiency

Regnology has released a pivotal report titled “The Agentic Gap: From Control to Intelligence in Regulatory Reporting,” which outlines how financial institutions can transition from experimental uses of artificial intelligence (AI) to fully integrated, high-impact applications in regulatory reporting. This report, based on research conducted with 276 practitioners across 22 countries, identifies a significant challenge—termed the “agentic gap”—that financial institutions face in moving from pilot programs to scalable, production-level AI solutions.

The urgency of addressing this gap is underscored by findings from Oliver Wyman, which indicate that regulatory reporting consumes 1% to 3% of total bank expenditure. A substantial portion of this expenditure—between 30% and 50%—is tied to internal process management, revealing a considerable opportunity for cost savings through agentic workflows. Regnology estimates that 15% to 25% of reporting costs could be optimized by adopting these advanced AI systems.

Despite widespread interest, with 87% of surveyed institutions actively exploring or piloting AI initiatives, only 8% to 15% of these organizations have successfully integrated AI into their reporting processes. This disparity highlights a common constraint: while many institutions have the resources to experiment, the path to reliable, production-ready AI is fraught with challenges, primarily related to data governance and the regulatory framework rather than technological limitations.

Rob Mackay, CEO of Regnology, emphasizes that while banks are inherently cautious—especially in areas with minimal tolerance for error—this caution can hinder the adoption of innovative solutions. The report suggests that the real challenge lies not in the technology itself but in finding professionals who can translate complex regulatory requirements into actionable AI applications. This skill set is rare, and Regnology positions itself as a partner to help institutions navigate this complexity.

The report offers a practical framework for financial institutions to assess their AI readiness and prioritize workflows that will yield the highest impact. It encourages organizations to baseline existing processes, design governance structures, and match the authority granted to AI systems with the risk associated with specific reporting tasks. This approach ensures that outputs are traceable and compliant with evolving regulations, such as the EU AI Act.

Linda Middledith, Chief Product & Engineering Officer at Regnology, elaborates on the concept of agentic AI, which encompasses a range of capabilities from interpreting data to executing tasks under human oversight. This nuanced understanding allows institutions to tailor AI applications according to their specific needs and regulatory environments.

In response to the findings, Regnology has developed the Regnology Intelligence (RGI) layer, which integrates AI-assisted decision support with agentic workflows, ensuring human oversight throughout the reporting process. The company will further explore these themes at the upcoming RegTech Convention, which will focus on unlocking intelligence in reporting and risk management.

As financial institutions grapple with the complexities of regulatory compliance, the insights from Regnology's report signal a critical shift in the industry. The move towards agentic AI not only promises significant cost savings but also enhances operational efficiency and compliance accuracy. Institutions that successfully navigate the agentic gap will likely gain a competitive edge, positioning themselves as leaders in a landscape where regulatory demands continue to evolve. The ability to harness AI effectively will become a defining factor in the success of financial institutions in the coming years.