Given regulatory challenges, can AI and ML revolutionize financial services compliance?

By Pooja Sharma

Mission-critical AI and machine learning technologies address the need to do more with less.

CUBE, a global automated regulatory intelligence (ARI) and regulatory change management (RCM), has released a report analysing the biggest compliance challenges facing global financial services companies in the world today. The report features interviews with respected compliance and regulatory experts across the industry and aims to help inform strategic decision-making within the compliance function.

To explain the current situation facing financial services companies: “CUBE is committed to providing the highest level of service to our customers, and we look forward to working with them to bring the best of our technology to the market,” said Dr. Yin Lü, Global Head of Artificial Intelligence Products at CUBE. “The scale of change that financial services firms have experienced over the past few years has been nothing short of disruptive. Innovative technology, aggressive regulators and strong consumer demand for new products and services have driven fundamental change in the industry within a very narrow time frame.”

The report categorizes the top compliance issues into five key areas: (i) the pace of regulatory change, (ii) addressing risk, (iii) the ESG gap, (iv) data privacy and AI, and (v) tightening budgets and rising costs.

Managing regulatory change remains a challenge for most. CUBE's Regulatory Inventory, the largest operational regulatory inventory in the world, has tracked over 40 million regulatory issuances directly applicable to the banking sector since the 2008 financial crisis. Expanding regulatory scope has been a consistent concern, such as the ongoing revision of the UK's payments framework and the direction US regulators will take in cracking down on cryptocurrency actors, digital wallet providers and shadow banking services post-Brexit, creating immense complexity for compliance professionals across the financial services industry.

Dr. Yin Lü emphasizes the importance of proactively staying ahead of risk in order to mitigate the ever-increasing number of fines being issued for non-compliance. He said: “The past 12 months have seen several enforcement trends emerge as regulators crack down on poor record-keeping, cryptocurrency fraud and weak corporate governance. As a notable example, fines for unmonitored phone use have totaled more than $2 billion since 2022. It's clear that staying ahead of ever-changing compliance requirements will benefit your bottom line.”

The report highlights the widening divide on ESG issues and how confusing this can be for compliance professionals who face the daunting task of guiding boards and CEOs through a multitude of conflicting demands and evolving standards.With a lack of clarity on how the financial services industry can best meet ESG expectations in different jurisdictions and a widening geopolitical rift adding fuel to the fire, it's not surprising that non-compliance is becoming increasingly common, given that there are more than 600 active ESG standards and frameworks.

Concerns regarding all aspects of data management, security, and privacy remain key challenges. Privacy laws have expanded significantly since 2023 as regulatory pressure to protect consumer personal data has increased. Compliance teams are being asked to implement complex frameworks that continue to evolve across international jurisdictions, and AI is proving to be an invaluable tool.

Dr Yin Lü explains: “Practices such as horizon scanning and data mapping using AI and machine learning techniques have become mission-critical practices. These practices help organizations structure, classify and even understand the ecosystem of laws that apply to their processing activities based on the data they collect and how they use it.”

Additionally, AI can help solve a common problem facing compliance professionals working in the financial services sector: the need to do more with less. With profitability and valuations that were there before the 2008 financial crisis unlikely to return anytime soon, banks in particular must consider how technological advances in AI can cost-effectively transform functions such as compliance. “Ultimately, the best prevention against out-of-control compliance spend is to embed AI at the heart of regulatory change management,” says Dr. Yin Lü.

Yin adds, “We need to move to machine-driven, human-verified compliance workflows with continuous feedback loops to ensure models are consistent with the latest data. We need to rethink what compliance teams can do in terms of promoting financial stability and protecting both businesses and consumers.”