Data is essential to any financial crime effort but it’s not just about the volume of data, it’s about having the right data in the right place at the right time.

“Do not just collect data for the sake of it,” said Phil Coole of OakNorth. “It has to be useful and you have to make the data capture palatable from the customer point of view, such as

“If you encourage customers to control some features such as spending limits then that can take away some of the friction”

 

Vesa Suvila, Nordea

doing live checks during the journey, for example, rather than a more clunky process where they have to go off and do it later.” Vesa Suvila of Nordea suggested giving customers more control over their data and finances. “If you encourage customers to control some features such as spending limits then that can take away some of the friction,” he said.

Our panellists stressed, again and again, the need to be able to bring multiple sources of data together to create a rich and holistic view of the customer. “If you look at a transaction or a KYC check on its own without any context, it’s very hard to tell if it’s definitely suspicious or not,” said Adam McLaughlin of NICE Actimize. “But if you start wrapping all those data points together you can start getting some context about what’s normal for that customer and what’s abnormal and that enriched profile helps your system generate more high-quality alerts, start more high-quality investigations and hopefully send better quality reports to law enforcement to give them a head start. This is the change that’s really needed.”

This is good on paper but for many financial services organisations, it’s much harder to put the theory into practice because of the costs and a toxic tangle of legacy systems that inhibit data sharing. “There’s a gulf between the new technology and the data and what’s actually implemented in banks with their complex architectural landscape,” said David Wright, senior manager of economic crime prevention at Lloyds Banking Group. “It can be very challenging.”

“When you bring data together to fight crime, you get better commercial decisions and better lead generation”

 

Phil Coole, OakNorth

Phil Coole of OakNorth, however, said there are also clear business benefits to sorting out data. “When you bring data together to fight crime you get better commercial decisions and better lead generation,” said Coole. “When you think in this way, it’s easier to get budget and investment.”

AI: an essential part of the toolkit

“AI has proven itself and is no longer a nice-to-have, it’s essential.”

 

Adam McLaughlin, NICE Actimize

Fraud detection and financial crime prevention are proving a good testing ground for the emerging power of AI, advanced analytics and machine learning. “It’s no longer a buzz word,” said Adam McLaughlin of NICE Actimize. “AI has proven itself and is no longer a nice-to-have, it’s essential. If you implement it correctly it will help manage alerts, fraud financial crime detection and better investigation outcomes.”

“Data is your biggest asset…it has to be relevant and you mustn’t let it become stale or inaccurate.”

 

Adam McLaughlin, NICE Actimize

The building blocks of a successful AI deployment are first to understand what you’re trying to achieve: don’t do it for the sake of doing it. “Then it’s data, detection and investigation,” said McLaughlin. “Data is absolutely critical. It’s your biggest asset but you need to grab data that’s relevant and then once you have it, you mustn’t let it become stale or inaccurate. You need to be able to monitor and assess it in as near real-time as possible. Is it coming from the right data sources, can you validate those sources and it the data allocated to the right customer?”

When it comes to detection, it’s about using the data to understand the customer and what’s normal – and abnormal – for them. “Then you can assign better rules and look at what they are doing across networks so that when you have a suspicious activity alert it’s more likely to be suspicious rather than a false positive,” said McLaughlin.

Finally, investigation. “With AI you have the ability to predict and you can learn from the previous activity and previous investigations and see what the likelihood of a SAR is,” he added.

But technology isn’t a silver bullet. “It can be cost-prohibitive for some banks and its value really depends on the quality of your data,” said Phil Coole of OakNorth. “You can also become too reliant on technology and that can lead you to miss something happening in an area of your business not covered by AI.”

Beyond technology, our financial crime fighters welcomed increased collaboration with colleagues. The combination of fraud detection with anti-money laundering operations, so-called FRAML, is expected to help with data sharing, analytics and detection.

“We’re in the midst of a transition to bring fraud and AML closer together,” said David Wright of Lloyds Banking Group. “We don’t want different teams in different silos looking at different elements when it would be more powerful to have a holistic view. When data comes together we can generate a great deal more value from it.”

Wright said this collaborative approach might mean “being able to dial down on application fraud and let more customers in the door and then use our combined capabilities to monitor activity more closely and react if we see anything.”

“Education is critical. All the technology in the world will not crack this …so we need to help customers recognise and protect themselves from scams.”

 

David Wright, Lloyds Banking Group

All our panellists agreed that there is also a need for increased co-operation with customers, and a real push on education and awareness. “Education is critical,” said David Wright of Lloyds. “All the technology in the world will not crack this as the fraudsters are very adaptable and flexible at coming up with ways around it so we di need to help customers recognise potential scams.”