Compliance teams across the financial sector are facing unprecedented pressures as regulations multiply and expectations grow across jurisdictions. For years, compliance frameworks have relied on labour-intensive, manual approaches that are often slow and prone to gaps.
However, technology-driven change has accelerated dramatically, marking a turning point for how compliance is managed and modernised, claims AscentAI.
As Susan Schroeder, vice-chair of the securities department at WilmerHale, said, “building and structuring a multi-faceted or multi-jurisdictional compliance program is no mean feat.”
She added that modern regulatory environments have grown significantly more complex alongside evolving technology. Many firms are therefore turning to digital solutions that promise faster and more accurate control of regulatory obligations.
Supporters of RegTech argue that smarter technology is now essential to handle regulatory burdens. One industry publication 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.” This view reflects a wider shift in the market as financial institutions seek solutions that lower cost, speed up reporting and reduce the risk of human error.
Artificial intelligence has become one of the most influential drivers of digital transformation in regulatory compliance. Yet AI adoption is not without challenges. Security, privacy, and emerging AI governance rules pose new risks, including potential penalties if firms misuse AI. In particular, the EU AI Act applies to any bank or nonbank lender that uses AI as a key element of its operations, including third-party service providers based outside the EU. As the world’s first comprehensive AI law, it focuses strongly on issues such as fairness, bias and protection of rights—making it clear that compliance teams must understand not only regulation but also responsible AI deployment.
Experts increasingly describe AI in two distinct layers. On one side are mature and trusted technologies like machine learning (ML), natural language processing (NLP) and highly domain-specific generative AI (GenAI). These power many tools used today, from voice assistants to pattern recognition engines in healthcare. Their reliability and accuracy make them well suited to regulatory tasks. Fortunately, RegTech solutions are incorporating these proven AI capabilities while avoiding the more experimental uses that have attracted controversy.
This is particularly valuable in areas such as change monitoring, where institutions must track regulatory updates in real time. As one industry source 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.” AI and ML support the identification of applicable regulations, analysis of new obligations, and comparison of updated requirements with previous versions—tasks that once required extensive manual review.
ML is the most widely applied AI technique in regulatory compliance. It enables systems to recognise patterns and classify regulatory content. Crucially, the quality of ML depends on the data used to train it. Unlike mainstream AI systems exposed to unverified and sometimes misleading information, RegTech solutions draw only from regulatory publications produced by official authorities. By using restricted and trusted datasets, RegTech limits the risk of inaccurate interpretations or so-called AI hallucinations.
Alongside ML, NLP helps systems read and understand regulatory language at scale, enabling faster processing of written rules. GenAI, meanwhile, can summarise legislative updates and translate dense language into more digestible explanations, supporting compliance officers’ decision-making. No technology, however, should remove human oversight entirely. The best compliance platforms balance automation with expert review, ensuring contextual judgement remains central.
AI is now seen as a major opportunity for firms aiming to streamline regulatory change management, reduce manual workloads and establish a single source of truth across the business. While some AI deployments still raise ethical or accuracy concerns, carefully governed and domain-specific AI tools are proving highly effective. As organisations evaluate RegTech providers, they are being encouraged to examine how AI models are trained, which data sources they use, and how risk is controlled. Technology alone is not enough; confidence in regulatory integrity is the ultimate benchmark.
RegTech solutions that combine the strongest elements of modern AI with rigorous oversight can simplify reporting, improve accuracy and deliver assurance in a changing regulatory era. With the right approach, institutions can achieve the promise of digital transformation and strengthen trust in their compliance operations.
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