Can AI & ML revolutionise compliance in financial services amid regulatory challenges?


CUBE, a leader in Automated Regulatory Intelligence (ARI) and Regulatory Change Management (RCM), has released a report detailing significant compliance challenges faced by global financial services firms today. The report serves as a strategic resource for compliance departments, incorporating insights from esteemed compliance professionals and regulatory experts within the industry.

Dr. Yin Lü, CUBE’s Global Head of Product for Artificial Intelligence, describes the recent environment in financial services as tumultuous, driven by rapid technological advancements, stringent regulatory scrutiny, and intense consumer demand for new products and services, all within a compressed timeline.

The report categorizes the primary compliance issues into five key areas: the rapid pace of regulatory changes, proactive risk management, the complexities of Environmental, Social, and Governance (ESG) criteria, data privacy concerns, and the challenges of operating within tighter budgets and rising costs.

One significant point of concern is the expanding scope of regulations, exemplified by the constant updates to the UK’s payment frameworks post-Brexit and the U.S. regulatory bodies’ efforts to regulate cryptocurrencies, digital wallet services, and shadow banking. Since the 2008 financial crisis, CUBE’s regulatory inventory has tracked over 40 million regulatory documents affecting the banking sector, highlighting the complex landscape compliance professionals must navigate.

Dr. Lü emphasizes the importance of staying ahead of risks to mitigate increasing penalties for non-compliance. She notes that recent enforcement actions have focused on lapses in recordkeeping, cryptocurrency fraud, and weaknesses in corporate governance, with fines related to unmonitored phone usage topping $2 billion since 2022.

The report also discusses the growing ESG divide, noting the difficulty compliance officers face due to conflicting demands and evolving standards across various jurisdictions. With over 600 active ESG standards and frameworks, achieving compliance is increasingly challenging.

Data privacy remains a critical concern, with privacy laws expanding significantly since 2023 under heightened regulatory demands to protect consumer data. AI and machine learning are invaluable in helping compliance teams manage complex international frameworks through horizon scanning and data mapping.

Furthermore, Dr. Lü highlights the pressure on compliance functions to do more with less, suggesting that integrating AI into compliance processes is crucial for managing costs and enhancing efficiency. She advocates for transitioning to machine-driven and human-validated compliance workflows to maintain alignment with the latest regulations and reimagines the potential of compliance teams to enhance financial stability and protect businesses and consumers alike.