survey, 57 per cent reported that they are using ai applications in risk management and compliance areas, including anti - fraud and anti - money laundering applications. in customer engagement, 39 per cent of firms are using ai applications, 25 per cent in sales and trading, 23 per cent in investment banking, and 20 per cent in non - life insurance. by and large, firms reported that, properly used, ai and ml would lower risks - most notably, for example, in anti - money laundering, kyc and retail credit risk assessment. but some firms acknowledged that, incorrectly used, ai and ml techniques could give rise to new, complex risk types - and that could imply new challenges for boards and management. challenges of ai and ml for boards let me suggest that there are three challenges for boards and management. the first challenge is posed by data. as any statistician knows, the output of a model is only as good as the quality of data fed into it – the so - called “ rubbish in, rubbish out ” problem. of course, there are various techniques for dealing with this problem, but fundamentally, if there are problems with the data used – be they incomplete, inaccurate or mislabelled – there will almost certainly be problems with the outcomes of the model. ai / ml is underpinned by the huge expansion in the availability and sources of data : as the amount of data used grows, so the scale of managing this problem will increase. further, there are complex ethical, legal, conduct and reputational issues associated with the use of personal data. for example, are data being used unfairly to exclude individuals or groups, or to promote unjustifiably privileged access for others? recent examples amongst retailers suggest that overly - personalised marketing can seem plain ‘ creepy ’. these questions require complex answers that are beyond my philosophical pay - grade. from a regulatory perspective, they are perhaps more directly a primary concern to the fca given its statutory objectives of consumer protection, but are also potentially relevant to safety and soundness, not least through their impact on reputation and, in turn, confidence. the data challenge is not limited simply to its selection and processing – but also to its analysis, and how inferences are drawn. ai / ml is driven by what seems to be objective historical data – but that itself may reflect longstanding and pervasive bias, as the example i used in the introduction showed. so there is a need to understand carefully the assumptions built into underlying

, to mop up a crisis without paying due consideration to the massive social costs that it causes. it follows that central banks should pursue both price stability and financial stability in a balanced and harmonized way to promote macroeconomic soundness. the central bank must make full use of its expertise in evaluating macro financial risks as well. and when necessary, it should work to counter these risks jointly with the government and the financial supervisory authorities. as a next step, from a global perspective, we need to work to enhance policy effectiveness through collective policy actions involving governments and central banks around the world. the world economy has become highly integrated, and the complexity and inter - connectivity of economic and financial phenomena have greatly increased. it has therefore become tremendously difficult for any one central bank alone to either prevent a crisis or deal with its aftermath. in this light, the recent crisis has triggered a realization among policy - makers worldwide of just how important policy cooperation is between the government, the central bank and the financial supervisory authorities. and the building - up of networks to support this cooperation is of course equally important. as i am sure you are aware, the construction of global financial safety nets was adopted as an agenda for the seoul g20 summit as a korean initiative. this may be seen as one prominent example of a collective policy action, having the characteristic of the supply of global public goods. lastly, i would point out the need for identifying exactly what influence monetary policy will have in the transformed economic and financial environment following the crisis. this crisis has had a devastating impact on the balance sheets of households, corporations and financial institutions, not to mention the government ’ s fiscal position. the experience of the crisis and the tightening of global financial regulations will also cause vast shifts in economic agents ’ behavior. furthermore, the changes in global macroeconomic conditions after the us federal reserve ’ s recent additional quantitative easing are looming as new challenges for central banks ’ monetary policy. in order to cope with this new world economic regime, we will need to devise necessary countermeasures to deal with the possible changes in the monetary policy transmission channels and the limitation on policy effectiveness. particularly, given that changes are always and everywhere accompanied by uncertainty, we should endeavor even more strongly to heighten the predictability and credibility of our monetary policy. closing remarks fellow central bankers, i hope this seminar provides an opportunity for constructive discussions on how the central bank contributes to economic and financial stability within the macroprudential policy framework. it will also be good