New technologies such as machine learning and blockchain could help solve the de-risking problem among banks globally and widen access to trade finance in emerging markets.
That’s according to a new study by Centre for Global Development, which assesses six new regulatory technologies – machine learning, biometrics, big data, know your customer (KYC) utilities, blockchain and legal entity identifiers (LEIs) – and their potential to address the de-risking problem.
De-risking has hit many emerging economies since the financial crisis. Amid fears of heavy penalties for breaching anti-money laundering (AML) regulations, the rising costs of conducting the requisite due diligence and the lack of confidence in the respondent banks’ risk control, financial institutions, particularly in the US and Europe, have pulled back from what they consider to be high-risk markets.
According to research by Accuity, a provider of compliance software that helps banks to reduce exposure to AML risk, the number of worldwide correspondent banking relationships, which are critical to cross-border financial transactions, has been in steady decline from 2009 to 2016, falling by 25% overall.
De-risking has had unintentional and costly consequences, especially in Africa, Central and Eastern Europe, and Asia Pacific. Among the biggest losers are small businesses that can’t access working capital or trade finance. As correspondents depart, they’ve left holes in the funding space, cutting credit lines and withdrawing finance.
The African Development Bank (AfDB) now estimates unmet demand for bank-intermediated trade finance of between US$110bn and US$120bn in Africa. De-risking is one factor behind the problem.
“Some policies that have been put in place to counter financial crimes have unfortunately had a chilling effect on banks’ willingness to do business in markets perceived to be risky – in part due to the high price of compliance,” says Vijaya Ramachandran, senior fellow at the Centre for Global Development and one of the study’s authors.
But, pointing to the new study, he says “regtech may be the solution to some de-risking woes”.
“What we’re seeing is that even as these policies are having an impact, financial institutions are coming up with solutions in the form of new cutting-edge technologies to help them comply better and faster with AML regulations,” Ramachandran says.
KYC utilities, for example, can reduce the amount of time correspondent banks spend on repetitive due diligence processes. Blockchain can improve the KYC data storage security.
Big data and machine learning can enhance correspondent banks’ ability to assess and manage risk through more sophisticated customer typologies and more accurate transaction monitoring. And biometrics can enable faster and more assured identification of individuals.
Over time, the study concludes, these technologies may alleviate some of the pressures on banks and “make holding correspondent banking accounts with clients in poor countries more likely”.
This enthusiasm about regtech is not new: GTR has previously reported on ways regtech can help the industry optimise compliance – a task that is still largely dominated by manual and mundane processes. A recent study found that banks could save £2.7bn a year by adopting machine learning and big data technology in their AML systems.
However, the argument that new regtech like machine learning and blockchain will bring banks back to de-risked markets is met with scepticism elsewhere in the industry.
“I don’t think technology is going to solve the problem. It’s a people’s, education and timing issue,” says Sean Norris, head of sales at Accuity.
He points to the fact that many of the de-risked countries, mentioning the likes of Afghanistan, Malaysia, Indonesia and Vietnam as examples, “haven’t got processes right for very basic things yet” and are still “far behind” when it comes to prioritising and implementing the Financial Action Task Force (FATF)’s guidelines and best practices for AML.
“When you’ve got a bank in Jakarta that is still relying of self-declaration of a person in a KYC process, how is that going to be acceptable for a western bank? I don’t think technology is going to solve a behavioural problem and different attitudes to AML controls,” he says.
Norris doesn’t deny the power of technology – after all, Accuity itself is a provider of AML software and is also exploring the use of machine learning to minimise the number of false positives. He also argues that de-risking is in fact driving the acquisition of better technologies by banks in Africa and Asia to upgrade their AML processes.
For example, more banks are looking to adopt Accuity’s sanctions screening solution to demonstrate that they are able to meet global standards of compliance and improve their ability to strike up new business relationships with financial institutions around the world.
But talking about the adoption of artificial intelligence and blockchain within banks in de-risked regions is “a stretch”, he argues, adding that the technologies being adopted are those that “have been around for a long time”.
“It’s really just to comply with the core aspects of AML,” he says. “Sanctions screening, for example, is something that England and the developed markets have been doing for the last decade, which they have now started to implement or operate in the emerging markets.”
New or old technologies, the industry may have to wait a bit longer to see the positive impact on the de-risking problem. But one thing is certain: those banks who take AML seriously have the best chance of re-establishing their broken relationship, Norris explains.
“The western banks are going to be a lot more comfortable when the banks are taking this seriously,” he says. “Compliance should never be a competitive sport, but when you’re talking about de-risking in these emerging markets, a lot of them are over-banked and so it becomes really hard for western banks to pick the right partner. They are going to pick the partner that is taking it seriously.”
Read the full study Fixing AML: Can New Technology Help Address the De-risking Dilemma?