Artificial intelligence is reshaping how financial institutions manage complex regulatory obligations, offering a way to replace labour-intensive procedures with faster and more reliable compliance operations.
For many firms, building a robust multi-jurisdictional compliance programme has always been a significant undertaking, often hampered by outdated manual workflows. As regulations have evolved over the past decade, the pace of technological development has created both new challenges and new opportunities for risk and compliance teams, claims AscentAI.
WilmerHale vice-chair of the securities department Susan Schroeder said, “Arguably the greatest advantage of RegTech is efficiency and the ability to take complex, manual processes and effectively streamline them, thereby freeing up resources.” Her remarks reflect a wider industry shift: financial institutions are increasingly seeking solutions that reduce operational strain while improving regulatory accuracy.
Artificial intelligence now sits at the centre of this transformation. However, its adoption is not without risk. Financial institutions must navigate concerns around privacy, data security, and the risk of breaching emerging AI-specific regulations. The EU AI Act, for example, applies to any lender or financial services provider using advanced technology as part of its core business, as well as third-party vendors supporting regulated firms. As the first major attempt to comprehensively govern AI, it focuses on areas where algorithmic decision-making intersects with fairness, bias, and individual rights. Many expect similar legislation to follow in other markets.
Despite these challenges, the most established AI technologies—machine learning (ML), natural language processing (NLP), and source-specific generative AI (GenAI)—are already proving invaluable. These capabilities are deeply embedded in everyday tools such as digital assistants and fraud detection systems, demonstrating strong reliability and accuracy. Within compliance, their value lies in the precision with which they can identify regulatory obligations, scan for updates, and interpret complex rule changes.
A recent report, From Data to Compliance: The Role of AI/ML in Optimizing Regulatory Reporting Processes, noted: “AI empowers financial institutions to monitor regulatory changes in real time, facilitating prompt adaptation to new mandates and mitigating the risk of non-compliance penalties.” This reflects the growing reliance on AI-enabled systems to track regulatory updates across markets and jurisdictions.
Machine learning remains the most widely deployed capability across RegTech platforms. At its core, ML identifies patterns within structured datasets to classify information and predict outcomes. In compliance, this allows platforms to map new regulations, compare updates against previous versions, and highlight relevant obligations. Crucially, ML systems in regulated industries rely on tightly controlled data sources—typically official documents published by supervisory authorities. This avoids the inaccuracy problems and “hallucinations” associated with large, unvetted training datasets.
NLP strengthens this process by enabling rapid interpretation of written regulatory text. It allows compliance platforms to break down lengthy documents, supporting the classification work performed by ML. GenAI then adds another layer by summarising regulatory updates into accessible formats, helping teams understand how new requirements may affect their organisation. Because these tools use highly curated data, they avoid the pitfalls often seen in more creative or open-ended generative AI applications.
Human oversight remains essential. While AI can automate previously burdensome tasks, compliance still requires context, judgement, and the ability to apply rules to business-specific situations. Vendors vary significantly in how they balance automation with expert supervision. Some rely heavily on machine-driven outputs, while others integrate human review to ensure accuracy and alignment with an organisation’s risk appetite.
When deployed thoughtfully, AI can transform compliance into a more streamlined, consistent, and proactive function. It centralises regulatory intelligence, reduces manual workload, and ensures teams receive timely updates on the issues that matter most. As firms continue to evaluate new technologies, the focus should remain on using AI capabilities at their most reliable—strengthening compliance without compromising accuracy or fairness. With the right safeguards in place, AI-enabled RegTech offers the dual benefit of operational efficiency and confidence in the integrity of regulatory processes.
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