Money laundering techniques have evolved significantly as criminals have leveraged technological advances. With business and society becoming more connected, financial criminals have adapted quickly. Meanwhile, increasingly stringent regulations and increased numbers of fines levied against banks mean financial services organisations are spending $180.9 billion annually on financial crime compliance, 62 per cent of which goes on labour expenditure in the Europe, Middle East and Africa region, the LexisNexis Risk Solutions Global Study found. All of this to recover less than 1 per cent of all the criminal proceeds, according to the United Nations.
Identifying this activity using traditional methods is extremely difficult. While banks have been seeking to adopt technology that does this more efficiently by simply doubling down on existing systems, anti-money laundering (AML) processes tend to remain significantly siloed, with a lack of cohesion between systems and departments. Legacy technology is a great inhibitor, slowing down banks at a time when open-source technology is enabling criminals to adapt and evolve more quickly. It’s imperative that banks find ways to look for vulnerabilities in systems more generally, and intelligently, while promoting closer alignment between departments.
“Banks have always kept information restricted, sharing it on a need-to-know basis between departments. Consequently, they’re unable to get a holistic view of their clients,” says Dr Janet Bastiman, head of analytics at regtech company Napier, whose intelligent compliance platform helps banks increase efficiency and minimise risk. “They tend to have multiple teams for onboarding, client life-cycle management, transaction monitoring and sales. Each of these teams can also be split geographically, so they don’t interact well or share data and insights. Things are quite literally falling through the gaps.
“The cybersecurity sector is very good at communicating new threats quickly, so everybody can immediately start patching. We need to have the same approach with money laundering. If somebody knows there has been suspicious activity, that information and how to recognise the new patterns needs to spread quickly to prevent recurrence. This isn’t happening because banks don’t have the systems, processes or technology to share the information and get a truly holistic view.”
Napier’s award-winning compliance platform provides the comprehensive view of customers that banks need. The company’s intelligent approach, which successfully combines big data technologies with artificial intelligence (AI), robotic process automation and machine learning, is applied to underpin policy, process and procedure. The Napier platform is fast, scalable and modular, meaning that financial institutions don’t need to replace their existing systems immediately and can build their sophistication incrementally.
The software helps different departments work together more effectively. As information runs through the system, it forms a top-level overview that then provides alerts to the appropriate teams at the right time. Client onboarding and KYC (know your customer) checks, for example, can be powered by contextualised information from numerous sources, and compared with behaviour from other customers and entities. A customer’s behaviour may look normal when viewed in isolation, but looking at it more holistically, next to all other sources of information, could show some unusual patterns.
“We want to make compliance officers sleep easily. With Napier, banks can better understand the fundamental interconnectedness of their data,” Bastiman adds. “You have the customers and how they’re connected to other customers and all their transactions, and being able to see that spider-like view really exposes any inconsistencies. But to do this you need that holistic view, a customer-centric approach, rather than just looking at siloed transactions.”
Taking this more intelligent approach also brings other benefits, including freeing up the time of compliance analysts who no longer have to sift through reams of transactions to try to spot patterns. Reducing the number of people required on these kinds of investigations, and feeding people with accurate information quickly, means humans can focus on more sophisticated tasks.
The technology is powering better explainability in a regulatory sense too. It’s not enough to say an issue was flagged by AI. Analysts need the detail in a simple, digestible language so they can explain to regulators exactly what caused concern. Historically, AI has not been successful here, with any explainability focused only on metrics for data scientists. Napier’s Client Activity Review has AI flags that show in plain English what the unusual transaction was in that period for the client, and why it was unusual. This enables anyone in the team to work with the insights, without requiring a data scientist to interpret the data.
“Criminals will always be trying to hide their activities and be one step ahead,” says Luca Primerano, Chief AI Officer at Napier. “As economics change in the world, whether that’s political or through major world events we’ve seen this year, it’s going to bring them new opportunities and also new challenges. The financial industry must really adapt to those challenges while stopping the opportunities for criminals as fast as they can.
“An AI engine can look at the transactional activities of customers much better than a human. It’s a completely independent set of lenses that can go through billions of transactions across multiple dimensions to detect anomalies, something that would take humans years to complete at great cost. The AI then collates that information into a simple summary of the top suspicious behaviours, including why they are unusual, so that a human analyst can make better decisions. Napier provides a completely unified solution with these capabilities, eliminating silos and combining everything together to gain that holistic view of customer behaviour. This helps banks work faster and smarter to fight financial crime, while at the same time reducing costs.”
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