office of the president, preparing for the future of artificial intelligence ; and financial stability board, artificial intelligence and machine learning in financial services ( basel : financial stability board, november 1, 2017 ), http : / / www. fsb. org / wp - content / uploads / p011117. pdf. - 2the three key components of ai - - algorithms, processing power, and big data - - are all increasingly accessible. due to an early commitment to open - source principles, ai algorithms from some of the largest companies are available to even nascent startups. 4 as for processing power, continuing innovation by public cloud providers means that with only a laptop and a credit card, it is possible to tap into some of the world ’ s most powerful computing systems by paying only for usage time, without having to build out substantial hardware infrastructure. vendors have made it easy to use these tools for even small businesses and non - technology firms, including in the financial sector. public cloud companies provide access to pre - trained ai models via developer - friendly application programming interfaces or even “ drop and drag ” tools for creating sophisticated ai models. 5 most notably, the world is creating data to feed those models at an ever - increasing rate. whereas in 2013 it was estimated that 90 percent of the world ’ s data had been created in the prior two years, by 2016, ibm estimated that 90 percent of global data had been created in the prior year alone. 6 the pace and ubiquity of ai innovation have surprised even experts. the best ai result on a popular image recognition challenge improved from a 26 percent error rate to 3. 5 percent in just four years. that is lower than the human error rate of 5 percent. 7 in one study, a combination ai - human approach brought the error rate down even further - - to 0. 5 percent. see, e. g., lael brainard, “ where do consumers fit in the fintech stack? ” ( speech at the fintech risks and opportunities conference, ann arbor, mi, november 16, 2017 ), https : / / www. federalreserve. gov / newsevents / speech / files / brainard20171116a. pdf. see, e. g., brandon vigliarolo, “ amazon ai : the smart person ’ s guide, ” techrepublic, august 21, 2017, https : / / www. techrepublic

of the emerging internal operational risk methodologies that institutions have pursued. our findings to date are consistent with the expectation that the ama typically results in a lower capital level than would be the case under the blunter measurement tools. with their new bottom - up, datadriven methodologies, banks are finding that the level of overall economic capital allocated to operational risk is not dramatically different from their old top - down methodologies, although the allocation across business lines often changes significantly. we believe that these methodologies and the resulting capital allocations for operational risk may be indicative of what we are likely to see once the new rules come into effect. supervisors must be willing to say that the size of the capital charge for operational risk under ama to some extent will depend on the development of industry practice and the experience and associated consensus that will evolve over time. in the interim, supervisors will need to engage banks in discussions about the likely size of their operational risk capital requirements. summary in closing, i will review the major points of my presentation. the proposed revision of the international capital accord is, at bottom, about improving risk management in banking, extending and building upon what most large banks have already begun to develop and what the market increasingly demands of large, complex banking organizations. it is a regulatory framework that seeks to develop a comprehensive and systematic approach to risk taking in banking. some have argued, however, that changing perceptions of risk will make basel ii risk - sensitive capital requirements pro - cyclical, exacerbating the real economic cycle. it is true that the required capital ratio will likely have a cycle ; but such a pattern will reflect genuine risk developments, and the more accurate measurement should be helpful to bank managers, supervisors, and the public. moreover, the behavioral response to more - sensitive capital requirements is likely to reduce the cyclical pattern in bank credit availability. in any event, the buffer capital held will absorb the cyclical movement in required capital. operational risk is not easy to measure, but it is a real risk that cannot be ignored. its proposed treatment in pillar i would likely result in more serious, and less uneven, attention. those banks that have conscientiously tried to measure and manage operational risk have been successful, and basel ii offers flexible techniques for trying different approaches. however, supervisors may well need to provide more guidance that will allow banks to estimate the size of the capital charge for this risk.