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The leading knowledge platform for the financial technology industry

A-Team Insight Blogs

Bank of England: Machine Learning set to Double in Financial Services

The Bank of England and the Financial Conduct Authority (FCA) have published a new report on ‘Machine Learning in UK Financial Services’ that predicts live machine learning (ML) applications will more than double within the next three years.

The report is the result of a joint 2019 survey between the two regulators covering over 300 firms including banks, credit brokers, e-money institutions, financial market infrastructure firms, investment managers, insurers, non-bank lenders and principal trading firms.

It found that in recent years, improved software and hardware as well as increasing volumes of data have accelerated the pace of ML development.

In many cases, development has passed the initial development phase, and is entering more mature stages of deployment. According to the survey, a third of ML applications are used for a considerable share of activities in a specific business area, while deployment is most advanced in the banking and insurance sectors.

“From front-office to back-office, ML is now used across a range of business areas,” confirms the report. “ML is most commonly used in anti-money laundering (AML) and fraud detection as well as in customer-facing applications (eg customer services and marketing). Some firms also use ML in areas such as credit risk management, trade pricing and execution, as well as general insurance pricing and underwriting.”

Although regulation is not seen as an unjustified barrier to ML deployment, some firms do stress the need for additional guidance on how to interpret current regulation. The biggest reported constraints are in fact internal to firms, such as legacy IT systems and data limitations. However, additional guidance around how to interpret current regulation could serve as an enabler for ML deployment.

The regulators plan to establish a public-private group to further explore some of the questions and technical areas raised.

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