Rob Gruppetta, Head of the Financial Crime Department at the UK Financial Conduct Authority (FCA), recently gave a speech at the FinTech Innovation in Anti-Money Laundering (AML) and Digital ID regional event, London about “Using artificial intelligence to keep criminal funds out of the financial system”. He considered whether machine learning and artificial intelligence (AI) techniques could help. Better transaction monitoring is not the only way AI can aid the fight against money laundering. The Financial Stability Board (FSB) published a report on 1 November about the impact of AI that identified other ways it can help. Examples include AI-driven anti-impersonation checks that evaluate whether photos in different identity documents match, and using machine learning to identify customers that may pose a higher risk and so warrant, say, a deeper probe into the sources of their wealth.
Mr Gruppetta said that the use of machine learning techniques does raise some questions.
- How can regulators become comfortable these systems are effective: if even the machine’s creators cannot know the reasons why the machine has made its recommendations, how can a regulator? The FSB explored this question in their report, asking how the lack of ‘interpretability’ and ‘auditability’ might pose dangers.
- Should machine learning complement existing transaction monitoring systems, or replace certain parts of the process, or even replace them entirely?
- What decisions are left for the humans?
He also said that AI has the capability to greatly amplify the effectiveness of the machine’s human counterparts, but it will be a constant work in progress. Any bank hoping for a black box in the corner that will sniff out the launderers will be disappointed, but the technology has the capability to better achieve keeping finance clean.