AI in risk management and the path forward for financial institutions, Joel Lange, Dow Jones Risk & Research

By Puja Sharma

Joel Lange, EVP & General Manager, Dow Jones Risk & Research, discusses the challenges of compliance and the potential solutions on offer from artificial intelligence

RegTech solutions provider Dow Jones’ Risk & Compliance recently introduced RiskCenter Advanced Screening and Monitoring (ASAM) – an AI-powered solution designed for financial crime prevention and third-party risk management. The tool streamlines risk management processes, enabling the screening of customers and third parties by financial institutions and businesses.

It is increasingly clear that the burden of anti-money laundering (AML) regulations is only going to get heavier, as Joel Lange, EVP & General Manager, Dow Jones Risk & Research, outlines in conversation with IBS Intelligence, first discussing the regulatory risks currently occupying compliance leaders: “Escalating geopolitical tensions between the West and China, coupled with wide-ranging sanctions against Russia and concerns around the financing of Hamas, Hezbollah, and Iran are some of the trends top of mind for compliance professionals right now. Coupled with new technologies, increasing global connectivity and ever more cross-border transactions, these developments have made risk management more costly, complex, and cumbersome than ever before for both banks and corporations.

“Against this backdrop, compliance teams are very much on the frontline in the fight against sanctions evasion, money laundering, terrorist financing, bribery, and corruption. These activities are occurring both locally and globally, and their perpetrators are increasingly sophisticated and difficult to detect. Now is not the time for complacency. Risk managers need to stay abreast of the latest trends, technologies, and regulatory frameworks to protect against these threats and reduce exposure to emerging risks.”

What tools and technologies are risk managers using to help them tackle financial crime?

“With the regulatory landscape in constant flux and millions of individuals and entities to screen against, a human simply cannot work fast enough to process the volume of information required to protect a company from regulatory, reputational, and ethical risks. We are therefore seeing more and more organisations turning to AI to analyse large volumes of data to identify and pinpoint patterns indicative of fraudulent or illicit activity.

“Advanced AI technologies can detect financial crime risk with a level of precision and speed that surpasses traditional methods. The ability to extract insights from both structured and unstructured data in multiple scripts and languages is one of the most exciting developments, helping organisations move beyond simple name matching against lists of sanctioned entities to a more proactive approach to risk management. “These emerging technologies are without doubt poised to play a pivotal role in the fight against financial crime, enabling organisations to stay ahead of emerging risks and quickly respond to potential threats in the dynamic financial landscape. But decision-makers need to ensure they are implementing and leveraging it in the right way – particularly in a compliance use case.”

How can risk managers be sure that the information they are reviewing is truthful?

“The proliferation of Generative AI (GenAI) has brought into sharp focus both the benefits and potential pitfalls of the technology for compliance purposes. While there is no question that AI presents significant advantages for compliance teams when it comes to informing decision-making at speed, the reliability of the technology ultimately hinges on the quality of its source data. “In an age of misinformation, knowing fact from fiction is becoming an increasingly difficult task. The rise of false or misleading information, particularly in regions plagued by geopolitical instability, remains a challenge that compliance teams must tackle. Transparency and explainability are crucial to addressing these concerns. Publicly available GenAI models often operate as opaque ‘black boxes’, providing users with little to no insight into the decision-making process.

Any organisation looking to implement the technology to aid risk management and decision-making needs to invest in compliance ready models which are reliable, safe and fully auditable. “With so many new tools and technologies at our fingertips, high quality, verifiable and licensed data sets from trustworthy sources will remain the bedrock of any best-in-class compliance program. Using datasets that have not been quality checked undermines the reliability of the system, which may introduce false positives or fail to surface crucial red flags.”

How are you seeing highly regulated industries adopt AI for compliance and where is it having the biggest impact?

“While AI can help organisations achieve more at scale, the potential pitfalls are well documented. Decision makers in highly regulated industries such as financial services have therefore erred on the side of caution when it comes to leveraging the technology. But as bad actors ‘innovate’ and find new ways to evade scrutiny, financial institutions need to arm themselves with cutting-edge tools and technologies to keep up with the pace of change.

“Negative news screening is one area where AI presents a huge opportunity for firms. Monitoring adverse media can uncover critical insights and red flags to help organisations have a better understanding of who they are doing business with, which is why the Wolfsberg Group, a non-governmental association of 12 global banks, recommends its use in the customer due diligence process. Advanced AI techniques such as Machine Learning and Natural Language Processing are able to extract insights from extensive volumes of unstructured newspaper text, providing further context for decision-makers and surfacing new risks as they emerge. In practical terms, the use of these technologies can reduce the time it takes to complete an adverse media check to as little as three minutes, whilst also improving the accuracy of the results.

“We are currently on the cusp of a wave of new regulations that will help safeguard against the challenges associated with AI which will boost confidence. The White House recently issued a wide-reaching executive order to mitigate the risks of this emerging technology, while in Europe, the EU AI Act charts a path towards the adoption of safe, transparent, and traceable technology. Ultimately, the decision to deploy AI in the financial services industry depends on our ability to effectively address the risks and challenges. Here at Dow Jones, we believe that a careful and considered approach will be fundamental to fully realise the potential of the technology, especially within the financial sector.”

What advice would you give to those seeking to deploy AI for risk management?

“It is crucially important to gain visibility into the data that is feeding your model to ensure it is both credible and copyright compliant. If your technology provider is simply scraping data from the free web, you are potentially violating intellectual property and copyright laws. We always say, particularly when it comes to journalistic content, do not risk committing a crime in your endeavour to combat financial crime.

“We are starting to see legislative developments in markets such as Australia and Canada designed to protect journalism in that regard—and that trend will only continue. So, while there are so many opportunities for efficiency, there is also a duty of care to ensure you are not falling foul of the law when trying to comply with financial crime regulation.”