Challenger bank accessing latest anti-money laundering technology through fintech

Challenger OakNorth is expanding its use of technology from a fintech supplier to ensure it meets anti-money laundering regulations.

The bank initially began using technology from ComplyAdvantage earlier this year, when it replaced incumbent supplier World-Check with the fintechs anti-money laundering screening platform. Using a ComplyAdvantage database, this service checks names of customers onboarding against politically exposed person (PEP) lists, sanctions lists and adverse media.

OakNorth, which has a policy of looking to the fintech sector for products and services, is now looking at automated transaction monitoring from ComplyAdvantage.

OakNorth got its UK banking licence in March 2015. It targets lending at high-growth small and medium-sized enterprises (SMEs) and now has over 140,000 savings customers with its pre-tax profits reaching £65.9m last year.

Although, unlike the big banks, OakNorth does not offer current accounts and therefore does not process huge numbers of transactions, it recognises that, like all other banks, it can be targeted by criminals laundering money.

ComplyAdvantage has a database and uses machine learning and natural language processing to automate real-time checks of various watchlists to support regulated organisations in managing their risk and preventing financial crime.

The technology supports OakNorth’s customer onboarding experience and ensures it meets anti-money laundering regulations.

“As a fast-growing business we are always looking for ways to innovate, and achieving robust compliance is a key factor in supporting our innovations,” said James Cashmore, chief risk officer at OakNorth.

“In ComplyAdvantage, we have a partner that understands our business objectives and their solutions seamlessly integrate into our systems. We look forward to finding new synergies as we grow our partnership going forward.”

Criminals use big banks to hide their dirty money, which is often linked to organised crime with funds being used to pay for assets to hide the money’s origin. According to the UN, about $2tn is moved illegally each year.

Under the threat of huge financial penalties, banks have turned to technology to detect money laundering activity. Today, machine learning and natural language processing are being used to replace manual work. Machines can read many more articles than humans and can automate anti-money laundering processes.

The cost of non-compliance justifies heavy investment in these technologies. In March this year, regulators in Sweden and Estonia imposed fines totalling €347m on Swedbank for breaching money laundering laws.

In the Netherlands, ING was fined €775m in 2018, after the regulator said the bank had failed to prevent the laundering of hundreds of millions of euros between 2010 and 2016.

And in 2017, Citigroup agreed to pay almost $100m and admitted to criminal violations as it settled an investigation into breaches of anti-money laundering rules involving money transfers between the US and Mexico.