, and encourage you all to consider and make use of its potential – though all the while we are keeping an eye on the risks, of course. the extent to which financial institutions are already using ml was addressed in a joint bafin ( bundesanstalt fur finanzdienstleistungsaufsicht ) - bundesbank consultation. banks and insurers are already employing machine learning in a number of areas, such as money laundering and fraud detection and in analyses used in lending processes, so mainly in risk management. companies are also using ml methods in sales and product pricing. ml is used only occasionally in internal pillar 1 risk models, but some banks and insurers see great promise in using it. already, ml is being used as an aid to validate internal models. the consultation shows that the areas in which ml methods can be applied are many and varied, and the potential is huge – extending far beyond the current area of application. the wide range of possible applications shows that “ big data ” also has “ big potential ”. for every institution, and for the stability of the financial sector as a whole. it is worth exploring and investing in that potential. but even though the term “ big data ” almost glosses over it, we ’ re not just talking about the quantity but also, at a very basic level, about the quality of the data. 2 data : quality, quality, quality the results of machine learning processes very much depend on the data they are fed with – as they say in it ( informationstechnologie ), “ garbage in, garbage out ”. if you feed a machine learning engine with data that are not varied enough, or are insufficient or fake, you are going to get incorrect results – and then run the risk of making the wrong business decisions. a problem arises when data are not sufficiently representative. take speech recognition, for example : even though this software is usually given a female name, such as alexa, siri and so on, it has a harder time recognising female voices than male ones. the reason is that alexa and siri are trained with databases in which male voices are overrepresented. another example, this one from the world of football, which again shows how dependent ml methods are on data : while matches were being held without spectators due to the coronavirus pandemic, one scottish football team used an aibased camera system to livestream its matches. this camera system

financial sector reform crucially depends on the timely and globally consistent implementation of agreed policies. as major reforms to address risks and strengthen regulation across the financial system have been adopted, it is becoming increasingly important to ensure that countries live up to their commitments. by means of peer pressure and transparency, we have to make sure that the measures necessary to improve the stability of the financial system are actually put into practice. a number of steps to ensure effective and timely implementation of internationally agreed reforms have already been taken. the results of numerous monitoring exercises are summarised by the fsb in regular scoreboards and public progress reports to the g20. in order to enhance the effectiveness of implementation monitoring, the fsb and important standard setting bodies have jointly established a coordination framework for implementation monitoring. in addition, the fsb monitors the implementation and effectiveness of international financial standards and policies via its peer review programme. peer reviews are an important tool to promote consistency, enabling fsb members to engage in dialogue with peers and share lessons and experiences. it is necessary to continue on this path. 6. closing remarks allow me to summarise : firstly, ongoing stress in the financial system and a weak economic recovery in many countries is no excuse to weaken our commitment to financial sector reform. secondly, today ’ s interconnected financial markets cannot effectively be regulated nationally. close international cooperation is warranted. thirdly, we must strike the right balance between achieving a level playing field and providing sufficient flexibility for the peculiarities of national financial systems. finally, rigorous implementation monitoring will be indispensable. as the old saying goes : trust, but verify. bis central bankers ’ speeches