About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

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

Subscribe to our newsletter

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.

Subscribe to our newsletter

Related content

WEBINAR

Upcoming Webinar: Best practices for regulatory reporting

Date: 16 July 2024 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes Regulatory reporting is a repetitive, time consuming and expensive business. At its best it requires robust data governance, automated data collection and reporting, standardised reporting formats, a centralised reporting system and a means to monitor and review regulatory change....

BLOG

Unlocking the Potential of AI in AML

By Steve Marshall, Director of Advisory Services, FinScan. AI has been increasingly used over the last few years to combat financial crime and money laundering. While it may not have lived up to its original billing as a silver bullet, some key lessons have been learned since those early days. Firstly, while AI has many...

EVENT

ESG Data & Tech Summit London

The ESG Data & Tech Summit will explore challenges around assembling and evaluating ESG data for reporting and the impact of regulatory measures and industry collaboration on transparency and standardisation efforts. Expert speakers will address how the evolving market infrastructure is developing and the role of new technologies and alternative data in improving insight and filling data gaps.

GUIDE

Practicalities of Working with the Global LEI

This special report accompanies a webinar we held on the popular topic of The Practicalities of Working with the Global LEI, discussing the current thinking around best practices for entity identification and data management. You can register here to get immediate access to the Special Report.