The UK’s financial regulator has said it will further the use of technology and big data in order to detect fraudsters.
Rob Gruppetta, head of the Financial Conduct Authority’s (FCA) financial crime department, told Chatham House how the regulator could use artificial intelligence to detect anomalies which could lead to a crackdown in fraud cases.
“The rise of machine learning is largely driven by the availability of ever larger datasets and benchmarks, cheaper and faster hardware, and advances in algorithms and their user-friendly interfaces being made available online,” he said.
“Crimes like money laundering – a secret activity that is designed to convert illicit funds into seemingly legitimate gains – is particularly hard to measure.”
Mr Gruppetta said that the deployment of AI allows the FCA to detect things which were previously difficult to detect, such as suspicious activity across different markets and venues. He said: “In this way, we’re squeezing the space that criminals can operate in…we are moving away from a rule-based, prescriptive world to a more data-driven, predictive place where we are using data to help us objectively assess the inherent financial crime risk posed by firms.”
He also spoke of how the regulator had used the technology to develop algorithms designed to catch out criminals.
“”We only ever use them as the first step in a rigorous, multi-layered risk assessment process to help us target the riskiest firms,” he told the audience, “consider building a risk model using algorithms: using a set of risk factors and outcomes, we could come up with a kind of mathematical caricature of how the outcomes might have been generated, so we can make future predictions about them in a systematic way.”