set out the uk ’ s approach to cryptoassets and distributed ledger technology in financial services4 ; examining challenges in cross - border payments with colleagues from the bank of canada and monetary authority of singapore 5 ; exploring how as set out by mark carney in his 2018 mansion house speech, “ new economy, new finance, new bank ”, available at https : / / www. bankofengland. co. uk / speech / 2018 / mark - carney - speech - at - the - lord - mayors - bankers - and - merchants - dinner - mansion - house. “ a platform for innovation ”, available at https : / / www. bankofengland. co. uk / speech / 2019 / mark - carney - speech - at - innovate - financeglobal - summit - 2019. i set out our ambitions for the fintech hub in my speech “ open to fintech ”, available at https : / / www. bankofengland. co. uk / speech / 2018 / dave - ramsden - speech - hmts - international - fintech - conference. see https : / / www. gov. uk / government / publications / cryptoassets - taskforce see https : / / www. bankofengland. co. uk / news / 2018 / november / boe - boc - mas - joint - report - digital - transformation - in - cross - border - payments all speeches are available online at www. bankofengland. co. uk / speeches financial services might evolve over the next decade as part of the bank ’ s future of finance project6 ; and analysing everything from the potential role of bigtechs in financial services to the implications of open banking and psd2. but instead of looking back, i want to stay faithful to the spirit of today ’ s session and look forward to the contributions the bank can make to the future of finance. fintech is one of the bank ’ s seven strategic priorities for 2019. in particular i ’ ll discuss three key areas of fintech hub focus in 2019 : payments ; unbundling ; and artificial intelligence. 7 payments the first area i ’ ll focus on is payments. while the bank is not nearly as old as the guildhall, this year we are celebrating 325 years as the uk ’ s central bank ; that includes 325 years of providing foundational payments services. payments have become increasingly digital in recent years, and there are now

one big win is the ability to produce structured data from a range of sources, the analysis of which traditionally required significant manual effort. over time it may be possible, for example, to train tools to recognise business lines via their numerical characteristics and patterns, and their unstructured data alongside structured regulatory returns. ml also allows documents with similar characteristics to be classified together and analysed, either within or across banks. for example, it could be used to follow the escalation trail from the most junior to the most senior committees. this sort of work is labour intensive when performed by humans : aided by machines, supervisors could in future devote time to those areas where humans have a comparative advantage. setting a supervisory strategy without effective communication is pointless, as we rely on the firms to take actions to mitigate the risks. to achieve complex supervisory outcomes – which often require significant, multi - year remediation by firms – boards and senior management of firms have to understand the context and rationale for what we are trying to achieve, as well as what we would deem to be a successful outcome. so getting our communications right is key. but how clear are those communications? firms have developed a wide range of more - or - less polite methods for providing us with feedback on the letters we write to them. but letter writing is an art rather than a science, and evaluating objectively how clear we are does not lend itself easily to traditional forms of quantitative methods. advances in ml, all speeches are available online at www. bankofengland. co. uk / speeches however, are helping. we recently analysed the letters we write to firms on the key risks they face and our supervisory strategy. we quantified a number of qualitative features of these letters, for example, how blunt we are in our messaging, how personal we are in terms of to whom we address the letter, and the overall sentiment expressed by the letter. we then used an ml model called random forests to detect whether, for example, the pra writes to firms differently than the prior regulator, the fsa. ( we do. ) 10 on the back of that project, we have built an app that now enables supervisors to analyse their written communications. supervisors can use the app to analyse any of their draft documents before they are sent to firms. iv. conclusion advanced analytics, machine learning and ai seem to be everywhere now – from image and voice recognition software to driverless cars and health