among some european politicians, to develop certain critical technologies on european soil. tremendous effort has been put into developing european regulations to manage these and other digitalisation - related risks. so that european citizens and businesses can take full advantage of new technologies, safe in the knowledge that the risks are well managed. 1 / 2 bis - central bankers'speeches large digital service providers, such as cloud providers, are set to become subject to european oversight, for example. and supervision of crypto service providers is being expanded. however, developments are happening rapidly, and the challenge is to be able to reap the benefits of innovation while keeping out the bad stuff. of all innovations, generative artificial intelligence is undoubtedly the most exciting : with the emergence of incredibly capable generative models and dramatic advances in computing power, we might very well be on the verge of a new technological revolution. who knows soon we can all paint like rembrandt. also here, we must make sure to maintain a healthy balance between harnessing the benefits of innovation while mitigating the risks. when it comes to innovation, some regions, like the us, have traditionally focused more on the opportunities side, with a regulatory environment that's conducive to business innovation. we europeans tend to focus on the risks and call for regulation. but falling behind in adopting new innovations is a significant risk too. so i would call for a balanced approach, and warn against constraining ai - driven innovation too much but that doesn't relieve us of the obligation to monitor the risks that come with it. many of the potential risks of ai may seem new, but if you look beneath the surface, they are strikingly similar to traditional financial risks. risks that we are familiar with. we already have frameworks to assess concentration risk, third party dependence and interconnectedness. this is good news. of course, it's not a simple copy - paste exercise. we may see new forms of interconnectedness in the financial system. for example, autonomous trading agents may interact to create new dynamics in financial markets. and technology that can be used to paint like rembrandt also offers possibilities for creative fraud, from phishing to identity theft. so the nature of the risks may not be different, but the crooks are getting better. that means we are entering a new phase of the never - ending race between risk and risk management. but we are entering this race from a relatively good starting point. ai is not

between banks and sovereign is that banks tend to overinvest into bonds issued by the home government compared to a well - diversiﬁed international bond portfolio ( de marco and macchiavelli 2016, horvath, huizinga, and ioannidou 2015 ). to what extent this pattern reﬂects a “ home bias ” in banks ’ investment portfolios is hard to assess, given that investment patterns depend on preferences, incentives, regulations, and transaction costs. the regulatory treatment of sovereign debt certainly affects portfolio choices of banks ( deutsche bundesbank 2014, 2017 ; kirschenmann, korte and steffen 2017 ). under current bank capital regulations, exposures of banks to sovereign debtors in the country ’ s own currency are assigned a risk weight of zero. in addition, these claims are exempted from limits on large exposures that would otherwise apply to large exposures to non - sovereign entities. similar exemptions apply to liquidity regulations. yet, claims on governments are not immune to the risk of default or of illiquidity. c ) implicit subsidies and systemic risk implicit guarantees for liabilities of ﬁnancial institutions are a key channel through which private and public debt are linked. they are contingent liabilities for the government which can turn into explicit payment obligations in times of crisis. quantifying this implicit subsidy and thus the expected bailout that debt holders expect to receive is not an easy task. funding costs advantages of banks which are deemed “ too big to fail ” ( tbtf ) may serve as a proxy ( siegert and willison 2015 ). the size of the funding cost advantage for a bank depends on the expected probability of default, the loss given that a default has occurred, and the expected recapitalization through the government. the probability of being bailed out, in turn, is inﬂuenced by factors such as the resolution regime and the ﬁscal capacity necessary to make the implicit guarantee credible. financial institutions that are deemed “ too - big - to - fail ” are indeed a recurrent theme in the history of ﬁnancial crises. individual banks can become too big, too interconnected with the rest of the ﬁnancial system, or too complex to disorderly exit the market. in 2011, g20 members thus agreed on reforms addressing the “ systemic and moral hazard risks associated with systemically important ﬁnancial institutions ” ( fsb 2011 ). three sets of policies have been implemented