This joint Bank of England and FCA report presents findings and analysis of the 2022 machine learning (ML) in UK financial services survey.
- a quantitative overview of the use of ML
- the ML implementation strategies of firms
- approaches to the governance of ML
- the share of ML applications developed in house or by third party providers
- respondents’ views on the benefits of ML
- respondents’ views on the risks of ML
- perspectives on constraints to development and deployment of ML
- a snapshot of the use of different methods, data, safeguards performance metrics, validation techniques and perceived levels of complexity of ML
The report closes with a selection of ML case studies, describing a sample of typical use cases, including:
- insurance pricing and underwriting
- credit underwriting
- fraud prevention and anti-money laundering (AML)
This survey builds on the 2019 survey, the AIPPF final report, and the wider domestic and international discussion about the use of ML in financial services.
In publishing the findings of the ML survey, we demonstrate our commitment to monitoring the state of ML deployment, improve our collective understanding, and support the safe and responsible adoption of ML technology in UK financial services.