2024 financial crime predictions: From international conflict to emerging technologies

2023 saw financial crime risk professionals contend with increasing geopolitical turmoil, economic volatility, and rapidly changing criminal behavior. In 2024, with more than 40 national elections, a growing focus on terrorist financing, and continued technological development, these issues – and more besides – will come to a head. 

In this article, our regulatory affairs experts forecast three top issues that will shape compliance leaders’ in-trays in the year ahead:

1. Rooting out terrorist financing will drive greater scrutiny of transaction flows and alternative payment mechanisms

The war in Gaza, ongoing unrest in Nigeria, coups in West and Central Africa, and the military junta in Myanmar demonstrate that watchlists aren’t enough to cut off funding for terrorists and uprisings. More needs to be done to identify and stop the financing pipelines that are supporting violent and repressive regimes around the globe. The Financial Action Task Force (FATF) and the United Nations have identified cryptocurrencies and crowdfunding platforms as key sectors terrorists use to raise money, increasing the likelihood of regulatory oversight in the new year.

“The crowdfunding sector has created a fast and easy way for members of the public to raise money for everything from worthy causes to medical treatments and dream vacations. Unfortunately, these same platforms are also being used to channel money to some of the biggest terrorist organizations around the globe. Tech and financial services companies need to step up their efforts to accurately identify their customers and confirm where their money is really going,” said Alia Mahmud, Global Regulatory Affairs Practice Lead for ComplyAdvantage.

2. AI will move sanctions enforcement beyond watchlist screening to identify risk signals in the sanctioned individual’s network

Sanctions are one of the best tools governments have to deter financial bad actors, but enforcement needs to move beyond watchlist screening to implement enforcement based on connected risk signals. With ongoing conflicts in the Middle East and Ukraine, policymakers will re-examine the efficacy of their sanctions programs to increase the pressure on persons and entities connected to sanctioned officials who may be enabling them to evade restrictions. By looking at risk data points collectively – identity, business associations, transaction activity – banks and other financial institutions can identify a strong risk signal of suspicious activity. Solving financial crime isn’t just a screening problem; it is a network problem, and regulators will expect companies to leverage new technologies to treat it as such.

“With unlimited time and resources, financial institutions could uncover any and all risky connections a sanctioned person has. But that’s not realistic. Artificial intelligence (AI) combined with rich data, graph analytics, and oversight has the potential to create a defense network that would give sanctions the teeth to cut off the money that funds terrorists, wars, human trafficking, and other crimes,” continued Mahmud.

3. Discussion about AI will shift to managing bias, modeling, and transparency

The benefits AI brings to fraud and AML risk detection were such a focus in 2023 that adoption has grown significantly. As this continues through 2024, the conversation will shift to how and where these models are used, emphasizing training and transparency.   

“As we head into 2024, the question is no longer if companies invest in AI, but what kinds of skills their analysts need to ensure that the models they use are effective and that they can justify decisions that they make to auditors,” said Iain Armstrong, Regulatory Affairs Practice Lead for ComplyAdvantage. “Key skillsets such as data preprocessing, model performance monitoring and optimization, and experience in automated decision-making strategies will be in demand. Staff in existing anti-financial crime roles will benefit massively from gaining a base-level understanding of machine learning and AI. Companies that invest in staff training in this area will reap the dividends.”