The ECB Governing Council has increased its policy rates by 200 basis points since July: we have moved closer to the neutral rate which we estimate to be around 2%, and which we should reach at our next meeting on 15 December. Let us be clear: this rate rise is good news for banks and insurers, who have long been critical of low rates. Financial institutions want the rise to be orderly: it is, very much so; but this does not mean it should be too slow, or predetermined. It is still too soon to talk about a "terminal rate": we will decide what is necessary following a meeting-by-meeting approach; and we do not steer market rates, which are sometimes excessively volatile. The return of volatility in the markets, starting with commodity markets where margin calls reached historic highs this summer. In equity markets, after the corrections observed since the start of 2022, valuations remain relatively high. Fixed income markets are also showing strong volatility, with one extreme example being the September UK sovereign debt crisis: aside from a few specific factors, this was a reminder to everybody of the crucial importance of credible fiscal policies. In light of this market volatility, it is more important than ever that we protect customers. I would just like to say a word here on the increased transparency and justification of life insurance fees: in a speech to you alongside Jean-Paul Faugère, I called for progress to be made this year, with a particular focus on dialogue with insurers.
Managing Machines: the governance of artificial intelligence  Speech given by James Proudman, Executive Director of UK Deposit Takers Supervision  FCA Conference on Governance in Banking 4 June 2019  I am very grateful to Philip Sellar for preparing these remarks, and to Sadia Arif, Jamie Barber, Jas Ellis, Magnus Falk, Orlando Fernandez Ruiz, Anna Jernova, Carsten Jung, Tom Mutton, Lyndon Nelson, Jennifer Nemeth and Oliver Thew for very helpful advice and comments. 1  All speeches are available online at www.bankofengland.co.uk/publications/Pages/speeches/default.aspx  Introduction Consider the well-known story of one Big Tech company’s attempt to use artificial intelligence to improve the efficiency of its staff recruitment. The machine learning system reviewed job applicants’ CVs with the aim of automating the search for top talent. The company’s experimental hiring tool used artificial intelligence to give job candidates scores ranging from one to five stars. Within a year, the company realised its new system was not rating candidates for software developer jobs and other technical posts in a gender-neutral way. That is because the computer models were trained to vet applicants by observing patterns in CVs submitted to the company over a 10-year period. Most came from men, a reflection of male dominance across the technology industry. In effect, the company’s system taught itself that male candidates were preferable. It penalised CVs that included the word “women’s” as in “women’s chess club captain”. And it downgraded graduates of two all-women’s colleges.