[Plans to set up this Forum were announced by the Bank in June 2019 as part of our response to the Future of Finance report.] The purpose of the Forum is to further dialogue between the public and private sectors in order to better understand the use and impact of AI in financial services. The Forum, which is expected to run for one year, will consist of a series of quarterly meetings and workshops structured around each of three topic areas: Data, Model Risk Management, and Governance. In terms of membership, the Forum will draw on the knowledge and experience of 21 leading AI experts from across the financial and technology sectors as well as academia; the Forum also has observers from the Information Commissioner’s Office and the Centre for Data Ethics and Innovation and more may be invited. The goal is to ensure that the Forum’s design reflects a wide variety of views. The full list of members can be found on our website.
In a recent survey of the banks and insurers we regulate, conducted as part of our ongoing monitoring of the impact of COVID-19 by the Bank’s Fintech Hub along with colleagues from the PRA, around 45% of those firms that participated reported that the crisis has led to an increase in the importance of AI and data science applications for their future operations, with around 55% reporting no change, and none noting a decrease. The survey also looked at changes in firms’ investment plans and resource commitments for AI projects as well as areas where the crisis has had an impact on existing applications across different business lines. 2  All speeches are available online at www.bankofengland.co.uk/news/speeches and @BoE_PressOffice  2  While the use of AI has clear benefits in an increasingly data-driven economy, there are risks and challenges. And the impact of those benefits and risks will be felt at different paces and different depths at technological, social, corporate, and systemic levels. It’s useful to think of the risks and challenges in a hierarchical way, starting with those that may become apparent at the data level and building up to the level of models trained on those data; then, widening to the level of the firm, and finally, up to the level of the financial system as a whole. Overlaying this are the regulatory and legal challenges presented by AI.