Is automated KYC enough in the fight against fraud?

As the way we move and use money changes, fraud finds new ways to fester. With reports of fraud increasing year-on-year, is automated KYC enough in this long-standing fight?

A recent post by RegTech firm PassFort examined the current fight against fraud and the technologies being used to put out the financial fires.

While ways of tackling financial crime and improving and increasing all the time, there is still almost unanimous agreement that the industry is losing the battle. For example, more than $937m in fines were issued in the first half of 2021.

According to PassFort, many criminals tend to use repeat tactics, which means that certain types of fraud are being uncovered more often and that affects the statistics. However, the firm noted that instances are increasing.

Despite the fact huge amounts of time, resources and money are being put forward to prevent fraud and money laundering, it is not having the impact that the industry would of hoped for. While banks and financial institutions are showing signs of progress, the fraud war is being fought on a number of fronts.

PassFort said, “Perhaps it’s naïve to expect the war against financial crime could ever be won. The nature of criminals is to spot a chink in the financial armour and adapt their plan of attack. It doesn’t seem feasible that financial crime could be eradicated.”

Developments including the rise of FinTechs and neobanks – which has created more ways to launder money and commit fraud – as well as more cross-border criminal activity, have left many financial services and regulators struggling to keep up for financial crime and fraud prevention.

With this considered, how can the industry get the upper hand? According to PassFort, one of the hardest tasks criminals are facing is getting their money into the banking system.

The company said, “It’s incumbent on banks to know their customers and to stop their systems being used to launder funds. Regulatory scrutiny has improved AML standards in this regard. Information sharing has also improved, with law enforcement, regulators and institutions working together to solve problems. And technology is playing its part too – making KYC and AML processes more efficient and effective. If regulation, technology and information sharing can come together to stop criminals gaining access to financial services, problems can be nipped in the bud.”

While KYC and AML processes and helping stop criminals secure access to financial services, is it enough? And is automation being taken too far?

PassFort cited a Dear CEO letter published by the Financial Conduct Authority in 2021 which criticised how banks were failing on some of the basics of financial crime compliance, with compliance taking some of the blame.

“The thrust of the letter was – yes, it’s fine to have AI and data analytics, but it’s still important to do the basics. Know your customer; understand your client, otherwise automation simply introduces more risk because people sit outside an algorithm or suspicious activity goes undetected,” underlined PassFort.

The RegTech underlined that while technology is great at making KYC processes more efficient, 100% automation is rarely optimal when it comes to understanding the nuance of criminals and how they operate.

In some cases, automation is optimal to use, especially in automating some aspects of AML and counter-fraud, as well as AML checks for politically exposed persons and sanctions. In addition, with criminals tending to employ repeat activities and automation being good at seeing repeated activity, automation is beneficial in this respect.

PassFort concluded, “But criminals tweak and evolve practices and identifying when a new type of fraud emerges may be harder to automate. Professionals can be invaluable in the detection process and in making sure an institution spots new types of financial crime. Automation helps optimise processes, but people and cognitive investigation are crucial to understanding the difference between customers and criminals in a nuanced way.

“AI models definitely aren’t able to predict behaviour yet. There is a balance to strike between making progress through deployment of technology and ensuring people are available to make risk-based decisions and identify new types of fraud.”

Find the full post here.

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