Articles

The next UK pandemic: financial fraud and firms increase in use of artificial intelligence to detect it

Finance firms are stepping up their investments in artificial intelligence (AI) and machine learning (ML) as part of their anti-money laundering (AML) investments.

Covid-19 and the disruption it brought to the global economy has triggered a sudden increase in financial crime, with money laundering a threat to society.

The UN estimates that up to $2tn is moved illegally each year. Criminals use big banks to hide money, which is often linked to organised crime, with funds being used to pay for assets to hide the money’s origin. In the UK, the National Crime Agency (NCA) estimates that money laundering costs the country’s economy £24bn each year.

According to a study from KPMG, software company SAS and the Association of Certified Anti-Money Laundering Specialists (ACAMS), a third of finance firms are accelerating the use of AI and ML in their AML strategies to fight the growing problem.

The study report, Acceleration through adversity: The state of AI and machine learning adoption in anti-money laundering compliance, questioned 850 ACAMS members worldwide.

Over half (57%) of respondents have either deployed AI or ML into their AML compliance processes, or are piloting AI solutions or plan to implement them within 18 months. “As regulators across the world increasingly judge financial institutions’ compliance efforts based on the effectiveness of the intelligence they provide to law enforcement, it’s no surprise 66% of respondents believe regulators want their institutions to leverage AI and machine learning,” said Kieran Beer, chief analyst at ACAMS.

“While many in the anti-financial crime world – the regulators and financial institutions alike – are just coming up to speed on these advanced analytic technologies, there’s clearly shared hope that these tools will produce truly effective financial intelligence that catches the bad guys.”

The two main reasons for adopting AI and ML in AML processes are to improve the quality of investigations and regulatory filings, cited as the main reason by (40%) and to reduce false positives and resulting operational costs, according to 38%.

In the case of money muling for example, AI would go a long way in detecting and investigating cases. More than 700 “money mule” transactions totalling €5 million moved through Irish bank accounts in the first half of the year, according to new industry figures, with the majority of incidents involving 18- to 24-year-olds.

FraudSmart, a fraud awareness initiative led by the Banking & Payments Federation Ireland (BPFI), urged young people and their parents to be wary of the dangers posed by the phenomenon and the “lifelong” consequences that can result.

“Money muling” is the name given to situations where people agree to open a new bank account in their name in order to receive a money transfer or series of inbound payments on behalf of a criminal operation.

Acting as a money mule is itself a criminal offence under the Criminal Justice (Money Laundering and Terrorist Financing) Act 2010 and can carry up to 14 years’ imprisonment, as well as making it difficult for “mules” to access financial services for their own purposes in future.

FraudSmart said transactions like these typically begin after the person receives an unsolicited email or social media message that promises easy money for little or no effort.

Another example where AI would prevent fraud is investment fraud. When a customer walked into a branch of TSB and asked to transfer £250,000 to a new fixed-income investment account, the staff went through their usual procedures. Was the customer sure he wanted to do this? He was adamant. An experienced investor, he showed them that the investment scheme was run by a firm registered with the Financial Conduct Authority (FCA). When the branch manager emerged for further checks, the customer became irate. He was frustrated that TSB’s workers did not trust his judgment.

So, in line with his wishes, the bank transferred the funds.

Three months later, as the first interest payment became due on the investment, it turned out that the firm no longer existed. The customer had been the victim of a sophisticated scam.

He was luckier in another sense. TSB, owned by Spanish bank Sabadell, is the only high street lender that guarantees to repay customers who fall victim to such fraudulent activities, which are sweeping the financial services industry.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s