Hence advances in AI are often associated with Big Data and the recent huge advances in the volume and variety of data available (see Figure 1). As the sophistication of algorithms and volume of data rise, the uses of AI in every-day life are expanding. Finance is no exception. In this speech I want to explore the impact of AI and advanced analytics more broadly, on the safety and soundness of the firms we supervise at the PRA, and how we are starting to apply such technology to the supervision of firms. In particular, I want to explore the seeming tension between the PRA’s supervisory regime that is firmly centred on human judgment, and our increasing interest and investment in automation, machine learning and artificial intelligence. II. CHANGING THE NATURE OF THE RISKS WE SUPERVISE  Like many other firms, banks are looking to harness the power and speed of AI. If you were to take some parts of the media at face value you might be tempted to conclude that a revolution is underway. There are plenty of examples of innovation to point to – from the use of ML-driven financial-market trading algorithms; to the introduction of online banking platforms that generate alerts to customers on trends and irregularities in their spending habits; to new apps that suggest switching utility providers to the cheapest provider.1 On closer inspection, however, the situation seems rather less revolutionary and more evolutionary.
(n.d.)  8  All speeches are available online at www.bankofengland.co.uk/speeches  8  References Amadxarif, Z., Brookes, J., Garbarino, N., Patel, R., and Walczak, E (n.d) Textual complexity in UK prudential regulation. Arnold, M (2018), HSBC brings in AI to help spot money laundering, FT available here: https://www.ft.com/content/b9d7daa6-3983-11e8-8b98-2f31af407cc8 Bholat, D., Brookes, J., Cai, C., Grundy, K., and Lund, J (2017), Sending firm messages: text mining letters from PRA supervisors to banks and building societies they regulate. Bank of England Staff Working Paper 688, available here: https://www.bankofengland.co.uk/-/media/boe/files/working-paper/2017/sending-firm-messages-text-miningletters-from-pra-supervisors-to-banks-and-building-societies Breslow, S., Hagstroem, M., Mikkelsen, D., Robu, K (2017), The New Frontier in anti-money laundering, available here: https://www.mckinsey.com/business-functions/risk/our-insights/the-new-frontier-in-anti-money-laundering Coen, J., Francis, W B., Rostom, M (2017), The determinants of credit union failure in the United Kingdom: how important are the macroeconomic factors? Bank of England Staff Working Paper 658, available here: https://www.bankofengland.co.uk/working-paper/2017/the-determinants-of-uk-credit-union-failure Financial Stability Board (2017), Artificial intelligence and machine learning in financial services, available here: http://www.fsb.org/wp-content/uploads/P011117.pdf Institute of International Finance (2018), Machine learning in credit risk, available here: https://www.iif.com/file/24725/download?token=FFv8Lhl1 McWaters, J (2018), The New Physics of Financial Services, available here: http://www3.weforum.org/docs/WEF_New_Physics_of_Financial_Services.pdf Sirignano, J., Sadwhani, A., and Giesecke, K (2018), Deep learning for mortgage risk, available here: https://arxiv.org/abs/1607.02470  9  All speeches are available online at www.bankofengland.co.uk/speeches  9