The 2008 financial crisis exposed both the fragility of global financial markets and a fundamental gap in how financial institutions understood and managed regulatory risk. The crisis acted as a catalyst, triggering a flood of new regulations and rapidly increasing compliance costs.
This presented an opportunity to evolve the financial industry’s approach to regulatory intelligence and analytics. This was the moment for RegTech.
A key focus was compliance infrastructures, but simply keeping pace with regulations isn’t nearly enough. To comply with regulations, there needs to be a deeper understanding, not just of their current requirements, but of their underlying patterns. How can you predict how regulations will evolve and how do you translate these into actionable intelligence? This is where Basel III comes into play, developed in 2009 due to the chaos of the financial crisis by introducing new capital requirements, liquidity ratios, and stress testing mandates that would reshape banking for the next decade and beyond. The phased rollout (2012-2025) created ongoing compliance complexity. This is where Artificial Intelligence (AI) has been fundamental, not just as a tool but as a foundational framework for achieving accurate and precise regulatory risk management.
Trust and technology
Introducing AI into regulatory intelligence has completely transformed the space, presenting an approach that can deliver something existing systems cannot – the ability to process large regulatory data sets, identify emerging risks, and access insights that human analysts cannot provide at such a large scale.
Succeeding in financial services is not just about having the best technology but proving that you have the best technology that doesn’t compromise on accuracy and that there can be trust in the way that the technology is used. This is important to highlight, particularly when dealing with AI, it’s a sober industry, the stakes are high and there is little margin for error.
AI has made leaps and bounds since 2009, as has the RegTech industry; this is why certifications and AI governance are crucial. AI safety and management is not a box to tick for compliance; it needs to be a fundamental shift for the industry and regulated industries need AI accountability.
Is certification an imperative?
ISO 42001 is the gold standard for AI governance, although there are other frameworks, the ISO 42001 framework is unique. It is the first international, certifiable standard specifically designed for AI management systems. To receive the certification, organisations must demonstrate a comprehensive understanding and control of their AI systems: explaining how it works, controlling how it operates and proving that AI usage operates safely and ethically. It is not optional; financial institutions using model risk management and algorithms must be transparent.
The process of certification requires that organisations examine all aspects of their AI systems, which include: data governance, bias detection, model validation, risk controls and explainability mechanisms. Companies have to prove that they can trace every decision their AI makes back to its source, maintain human oversight where it matters most and understand what the limitations are.
Why does it matter? It matters because AI in financial compliance is all about being accurate, fair and stable. If banks use your AI to assess regulatory risk or compliance obligations, you can’t afford to be wrong.
The proof is in the AI pudding
AI has had mass adoption and financial services as an industry is plagued with AI claims; each vendor promises that their AI capabilities are ‘revolutionary’, but how many can prove that? Marketing AI and the reality of AI need to align; there is a gap and it can become problematic in regulated industries.
The ISO 42001 certification provides a framework to separate genuine robust AI capabilities from marketing hyperbole by requiring strict documentation, independent validation and ongoing monitoring – it offers a clear standard.
Overstating AI functionality in financial services carries severe risks that extend beyond reputational damage. Misrepresenting AI functionality can result in regulatory penalties, operational failures and more fundamentally, unreliable AI destroys trust in a technology that has the genuine potential to transform compliance and risk management.
Moving forward
As AI is developing to become more sophisticated, regulators are becoming more prescriptive about how it’s used. Organisations that prioritise and invest in proper AI governance can only succeed.
Financial compliance will be shaped by AI systems that are powerful, transparent, accountable and most importantly, safe. Organisations that recognise the reality and act on it will thrive in an increasingly complex regulatory environment.
Despite the saturation of AI, the industry remains in the early stages of AI transformation. One thing is loud and clear: the organisations that succeed are the ones that pair AI innovation with dedicated governance.
John Byrne is the Founder and CEO of Corlytics