James Proudman of BoE on Governance of Artificial Intelligence

Mr. Proudman emphasized that a prudential regulator must understand how the application of artificial intelligence and machine learning within financial services is evolving and how the resulting risks can best be mitigated through banks’ internal governance and through systems and controls. Despite the plethora of anecdotal evidence on the adoption of artificial intelligence and machine learning, there is little structured evidence about UK financial services. To gather more evidence, BoE and FCA sent a survey in March to more than 200 firms, including the most significant banks, building societies, insurance companies, and financial market infrastructure firms in the UK. The full results of the survey will be published by the BoE and FCA in the third quarter of 2019. However, responses were returned in late April, so some early indicative results are emerging. 

Overall, the mood around implementation of artificial intelligence among firms regulated by BoE is strategic but cautious, said Mr. Proudman. Four-fifth of the firms surveyed returned a response; many reported that they are in the process of building the infrastructure necessary for larger scale deployment of artificial intelligence and 80% reported using machine learning applications in some form. The median firm reported deploying six distinct such applications and expected three further applications to go live over the next year, with ten more over the following three years. Barriers to  deployment of artificial intelligence seem to be mostly internal to firms, rather than stemming from regulation. Some of the main reasons include legacy systems and unsuitable IT infrastructure; lack of access to sufficient data; and challenges in integrating machine learning into existing business processes.

He concluded his speech by describing three principles for governance of artificial intelligence and machine learning, based on his observations. First, the observation that the introduction of artificial intelligence and machine learning poses significant challenges around the proper use of data, suggests that boards should attach priority to the governance of data—what data should be used; how should it be modeled and tested; and whether the outcomes derived from the data are correct. Second, the observation that the introduction of artificial intelligence and machine learning does not eliminate the role of human incentives in delivering good or bad outcomes, but transforms them, implies that boards should continue to focus on the oversight of human incentives and accountabilities. Third, the acceleration in the rate of introduction of artificial intelligence and machine learning will create increased execution risks during the transition that need to be overseen. Boards should reflect on the range of skill sets and controls that are required to mitigate these risks both at senior level and throughout the organization.

Related Link: Speech

Keywords: Europe, UK, Banking, Insurance, FMI, Fintech, Artificial Intelligence, Machine Learning, Governance, Big Data, FCA, BoE