Financial crime experts at a recent roundtable said there was no longer a distinction between AML and fraud efforts, signalling a shift in how the industry is approaching the fight against financial crime.

The roundtable discussion, held on the sidelines of Regulation Asia’s Fraud & Financial Crime conference, brought together experts from banks, technology firms, regulatory bodies and other government agencies to discuss key challenges and evolving strategies in the industry.

The roundtable focused on data sharing, shell company detection, and the increasing convergence of AML and anti-fraud strategies. A central message that emerged was that traditional data silos must fall to enable a more holistic and effective defence against financial crime.

Breaking down data silos

The roundtable participants emphasised the increasing importance of data sharing and collaboration in combating financial crime.

Holly Miller, Head of Anti-Fraud for APAC at Quantexa–a global AI, data and analytics software company pioneering Decision Intelligence–set the stage by highlighting the historical separation of fraud and AML teams due to practical reasons around objectives and data availability.

Miller pointed to the existence of data sharing initiatives around fraud, such as CIFAS, a fraud prevention organisation in the UK, and AFCX in Australia, but noted that sharing data around broader financial crime more broadly has been more challenging.

She emphasised the need for secure data sharing, where only authorised personnel can access the data, and stressed the potential for increased insight when intelligence is shared across a bank, across teams, and even across the industry. “There’s so much more insight that you get if you’re sharing intelligence,” Miller said.

Shell company detection

The detection of shell companies was identified as a major challenge. Participants noted the need for tighter controls around shell companies, particularly at the onboarding stage.

Marta Chowaniak, AML Solution Owner for APAC at Quantexa, presented a case study highlighting the use of shell companies in trade fraud and sanctions evasion, noting, “Shell companies are actually the entry points to many of the risks that we are looking for. Fraud, AML and sanctions – they are used for all of this.”

She further illustrated the point with a real-world example of a shell company facilitating trade fraud, disguising the source of funds, and ultimately disbursing those funds into mule accounts.

A senior banker participating in the discussion noted that his bank has incorporated machine learning models to identify shell companies and has implemented tighter controls at the onboarding stage. However, he acknowledged the difficulty of identifying shell companies before they begin transacting.

The difficulty of definitively identifying a shell company was discussed in depth, with participants acknowledging that it is not always black and white, and that it can be challenging to differentiate between legitimate and shell companies.

Convergence of AML and fraud

The increasing convergence of AML and anti-fraud efforts was another recurring theme. One senior banker said “there is no distinction between AML and fraud” due to the increasing overlap between mule accounts, scams, and money laundering. He noted that his bank is creating a single view for businesses and “everybody in the bank gets to see data across all these teams”.

Another participant highlighted a case where a bank employee was linked to organised crime and colluded to set up a network of mule accounts. This case demonstrated the convergence of cyber risks, fraud, and money laundering.

The need to move away from traditional, reactive transaction monitoring to more proactive, real-time monitoring was emphasised. Participants noted that traditional suspicious transaction report (STR) processes are not effective in stopping scams, as they are often too slow.

The intention of fraud prevention is to save money for the customer, whereas traditional monitoring is focused on identifying red flags and raising STRs. One participant noted that regulators in Singapore are pushing banks to move away from periodic monitoring (e.g. 60-80 day cycles) and closer towards real-time monitoring, especially for new accounts.

Navigating the regulatory landscape

The discussion also touched on the evolving regulatory landscape and the importance of engaging with regulators.

Participants noted that different regulators have different appetites for discussion and collaboration. Some regulators are very open to dialogue, while others are more prescriptive. The importance of having a good relationship with law enforcement was also emphasised.

The challenges associated with cross-border payments were also discussed. Participants noted the need for payment validation services – i.e. a ”confirmation of payee” service, but one that works globally – though they acknowledged the difficulties of implementing such services.

The discussion made one thing clear: passively reacting to financial crime is no longer an option. To effectively combat evolving threats, institutions must embrace proactive strategies – fostering collaboration, breaking down data silos, leveraging technology for real-time monitoring, and actively engaging with both regulators and law enforcement.

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Quantexa is a global AI, data and analytics software company pioneering Decision Intelligence to empower organizations to make accurate decisions from a trusted, AI-ready data foundation. Quantexa’s Decision Intelligence Platform enables organizations to uncover hidden risk, find new opportunities, and enhances operational performance with over 90% more accuracy and 60 times faster analytical model resolution than traditional approaches. An independently commissioned Forrester TEI study found that customers saw a three-year 228% ROI.

For more information, please visit www.quantexa.com or follow on LinkedIn.