That’s according to the latest survey from SmartSearch, which polled 500 decision-makers in regulated legal, property and finance businesses on a range of anti-money laundering (AML) compliance issues.
It revealed that more than one in three, 34 per cent, of firms in finance and banking had not changed their approach to new customers since the sanctions were imposed, rising to almost half, 47 per cent, of those in the legal sector.
The investigation also found that almost half, 45 per cent, of those surveyed rely on physical documents like passports or utility bills to identity new clients, rather than move to a digital onboarding process. This is despite around one in six, 14 per cent, admitting they were not confident in their ability to spot a fake document in person.
Martin Cheek, managing director of SmartSearch, said the study demonstrated the “worrying size of the challenge” in closing the AML loopholes which are being utilised by criminals.
He continued: “As the government increases its censures on companies for breaching compliance rules, some are continuing to risk fines and reputational damage by either failing to increase their surveillance in the light of sanctions or relying on outdated manual checks. Or both.”
Cheek emphasised that regulated businesses need to do more, which means embracing electronic verification which he suggested is “virtually impossible to fake”.
Getting the right systems in place
Sebastian Riemann, director of Virtus Private Finance, said that his firm has had no issues with money laundering in general as its systems “have been pretty strict for some time”.
He added: “There is a general move towards using online/digital processes which works especially well when not seeing clients face to face. For me personally I only work from referrals from existing clients and individuals I have known for a long time. I also do almost everything exclusively in person which limits the risk too.”
A report last year from FICO suggested that home working and the shift in consumer behaviour had presented new challenges in AML detection.
