Regnology report reveals AI's potential in Regulatory Reporting efficiency. Regnology's latest report unveils critical insights into the 'agentic gap' facing financial institutions as they move from AI experimentation to impactful deployment in regulatory reporting. Discover how overcoming this challenge can lead to substantial cost savings. Key facts. * 87% of financial institutions are piloting AI, indicating a strong industry shift towards automation. * Regulatory reporting costs 1-3% of bank expenditure; 15-25% could be reduced via AI workflows. * Only 16% of institutions have achieved production-level AI, revealing a significant agentic gap. * Manual processes dominate reporting, highlighting vulnerabilities in efficiency and error tolerance. * Regnology's RGI combines AI and human oversight, positioning it as a leader in regulatory tech solutions. Summary. 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. Entities mentioned. Oliver Wyman Rob Mackay Linda Middledith Mireille Adebiyi Organizations RegTech Convention Key concepts. Agentic Gap AI in regulatory reporting Governance in AI Operational load Cost of regulatory reporting Agentic workflows AI readiness Definitions. * Agentic Gap - The distance between testing an AI concept and relying on it within the reporting cycle. * Agentic AI - AI that can take on meaningful operational tasks under human oversight. * Regulatory Reporting - The process by which financial institutions report their financial status and compliance to regulatory bodies. * AI Readiness - The preparedness of an organization to implement AI technologies effectively. * Governance - The framework of rules and practices by which an organization ensures accountability and control over its operations. Use cases. * | Transitioning from AI pilots to production in regulatory reporting * | Embedding AI in financial institution operations * | Using agentic workflows to reduce reporting costs * | Implementing governance frameworks for AI systems * | Prioritizing high-impact workflows in regulatory processes * | Enhancing decision support with AI-assisted tools Frequently asked questions. What is the Agentic Gap? The Agentic Gap refers to the distance between testing an AI concept and fully integrating it into the reporting cycle. It highlights the challenges organizations face in moving from experimentation to reliable production use. How can financial institutions benefit from AI in regulatory reporting? Financial institutions can leverage AI to automate and enhance their regulatory reporting processes, potentially reducing costs and improving accuracy. The report suggests that a significant portion of reporting spend could be addressed by implementing agentic workflows. What role does governance play in AI implementation? Governance is crucial in ensuring that AI systems operate within established rules and frameworks. It helps organizations manage risks associated with AI, particularly in sensitive areas like regulatory reporting. What is RGI? RGI, or Regnology Intelligence, is a product developed by Regnology that combines explainability, AI-assisted decision support, and agentic workflows under human oversight. It aims to enhance the efficiency and reliability of regulatory reporting. What is the significance of the RegTech Convention? The RegTech Convention is a major event organized by Regnology that brings together industry experts, regulatory authorities, and financial institutions. It serves as a platform for discussing advancements and challenges in regulatory technology and financial regulation.

Regnology launches new AI platform to strengthen compliance and risk monitoring. Regnology, a leading regulatory technology firm, has expanded its AI capabilities with the launch of a new platform designed to support financial institutions in improving compliance, risk monitoring, and operational efficiency. The platform leverages artificial intelligence, machine learning, and advanced analytics to automate regulatory reporting, identify anomalies, and provide actionable insights for risk management. Financial institutions using the platform can expect streamlined regulatory processes, faster detection of compliance gaps, and improved decision-making, reducing both operational costs and regulatory risks. Regnology emphasizes that the AI-driven system is adaptable to evolving regulatory requirements, helping organizations remain compliant while efficiently managing resources. Industry experts note that integrating AI into regtech solutions enables proactive risk management and real-time monitoring, allowing banks, insurers, and fintech companies to respond quickly to regulatory changes and maintain operational resilience in a rapidly evolving financial landscape. Explore practical certification courses designed for banking, risk, insurance, compliance, ESG, AI, and emerging technologies professionals. Learn from industry experts and earn certifications from RMAI and BFSI Sector Skill Council of India. #Riskmanagementnews