many analysts, the domestic demand in emerging markets holds up. this situation could result in the country maintaining or even increasing the level of our exports to these markets. such could thus prop up the overall exports. remittances is a second important channel through which a slowdown in the us economy could impact on the domestic economy. latest data show that 1 / 3 of our land - based overseas filipinos are in the us. the diversification in deployment in terms of destination and quality of skills could, however, temper any slowdown in remittances. let me now turn to the third major risk that we face : the rise in global food and energy prices. food prices have gone up as a result of strong demand from china, india, and other emerging market economies that are experiencing rising incomes. poor harvests due to adverse weather conditions and increased biofuel production have also ratcheted demand for certain related food items. furthermore, just recently we saw oil price breach the $ 100 - a - barrel level. geopolitical tensions in the middle east, refinery bottlenecks, speculative activity, the weak us dollar, and the continued strong demand for crude oil all exerted an upward pressure on global oil prices. however, as global growth slows, we may see commodity price volatilities abate in the second half of the year. with these risks that i have just described being primarily global and largely not directly within our control, why do we believe that the philippine economy will be able to ride out these patches? the short answer is we have built up domestic buffers. what are these? one, we have built up buffers in our domestic financial system. the philippine banking system ’ s asset base has grown steadily over the last 6 - 7 years. the overall asset quality of banks continued to improve as well, with the npl ratio now moving closer to the pre - crisis level of around 4 percent. banks ’ overall capital adequacy ratio was also maintained well above regulatory and international standards, shored up by the increased issuance of hybrid financial instruments to strengthen their capital base. last year, we rolled out two reform packages aimed at improving the system ’ s ability to manage risks and competitiveness in a more globally integrated market environment – here i refer to the further liberalization of our fx market and the new derivatives circular. amid the heightened risks in the global financial markets last year, the banking sector has showed resilience. two, the

machine learning in risk models – brontobytes and brontosauruses speech delivered at the bundesbank - bafin fintech festival 19. 05. 2022 | berlin | joachim wuermeling 1 introduction 2 data : quality, quality, quality 3 supervisory approaches : a question of characteristics and explainability 4 conclusion 1 introduction ms roth, ladies and gentlemen, the brontosaurus, a long - necked 30 - tonne herbivore, is one of the most well - known dinosaurs and surely familiar to many of you as well. perhaps it was a fascination with dinosaurs that led to one of the largest units of data volume being called the brontobyte. and just like the brontosaurus, the brontobyte is also awe - inspiring ; it seems gigantic and somehow unmanageable and inconceivable. the brontobyte comes after the gigabyte, terabyte, petabyte, exabyte, zettabyte and yottabyte. one brontobyte equals around 10 to the 27th power of bytes, or a 1 followed by 27 zeros. this volume of data would be equivalent to the us ( united states ) library of congress 100 trillion times over ; every person in the world would have 12, 500 copies of this library. this is big data in the truest sense of the word. however, we have not yet entered the brontobyte era. right now, we are in what is known as the zettabyte era : in 2016, annual global internet traffic exceeded one zettabyte. around 1 million such zettabytes make up a brontobyte. we ’ re still a fair way off that mark. who is supposed to process all this information? this is where artificial intelligence ( ai ) and machine learning ( ml ) come into play, because they are capable of managing these data volumes. and in the financial sector, banking supervisors – bafin ( bundesanstalt fur finanzdienstleistungsaufsicht ) and the bundesbank – have a vested interest in this. you see, digital technologies can make individual banks more stable, through better analyses and data management or the use of advanced analytics in risk management. thus, ai and ml can create added stability for the financial system as a whole. we, as supervisors, therefore wish to act as enablers of the digital transformation. we support the use of ai