To implement Financial Compliance, UK Regulator gearing up to Use A.I., Machine-Learning

The Financial Conduct Authority, an independent U.K. financial regulatory body, is looking into the possible use of artificial intelligence (AI) and machine-learning tools to enforce regulatory compliance. Nick Cook, the FCA's head of data and information operations, said that the regulator was "still learning", and that feedback from a "call for input" from regulatory technology (regtech) firms was informing it about how to support the adoption of automated, digitized compliance.

"We are looking at the extent to which we can make parts of our handbook initially machine-readable and then fully machine-executable ... Effectively converting, probably initially our regulatory reporting rules, into truly unambiguous rules that machines can interpret and implement directly," he told an audience at London Fintech Week, a financial technology (fintech) conference, on Tuesday. "The idea being that we can put out rules which are written manually in ways that can be fully and unambiguously interpreted by machines," he added.

Cook added that the FCA was looking into the practical use of machine-learning to make better use of speech-to-text software, social media and media analytics.

Regtech (regulatory technology) is a subset of the financial technology (fintech) industry. Experts believe it could drastically reduce the cost of regulatory compliance, currently estimated to be around $80 billion globally.

A report published last October by the University of Hong Kong identified the regtech industry as a field capable of addressing risk in "real time" and increasing the efficiency of compliance.

"Regtech to date has been focused on the digitization of manual reporting and compliance processes, for example in the context of know-your-customer requirements," it said. "This offers tremendous cost savings to the financial services industry and regulators. However, the potential of regtech is far greater – it has the potential to enable a close to real time and proportionate regulatory regime that identifies and addresses risk while also facilitating far more efficient regulatory compliance."