##ries and investors may well affect the stability of the system. public authorities must carefully examine the changes induced by digital technologies and value innovative projects to preserve the stability, the efficiency, and the security of the financial sector. the complexity is increased by the fact that central banks are at once both users and producers of information and big data. proof of this is the collection of highly granular data on individual bank loans by the single supervisory mechanism ( the so called anacredit ), on daily money market statistical reporting by the european system of central banks, and on the trading repositories envisaged by the european market infrastructure regulation. the sheer amount of these granular data makes it clear that the necessary validation processes cannot be performed manually, but will require sophisticated algorithms and techniques such as machine learning or artificial intelligence. central banks should master these new technologies. the bank of italy has created an internal multidisciplinary team on big data which includes economists, statisticians and computer scientists from different departments, working in close cooperation with the directorate general for information technology. the team has built a hardware and software infrastructure in order to deal with different kinds of big data for both macroeconomic and microeconomic issues. some of the results will be discussed during this workshop. the analyses focus on using unstructured textual data from social media, in particular twitter, to compute inflation expectations4 or to gauge retail depositors ’ trust. 5 see c. angelico, j. marcucci, m. miccoli, and f. quarta, ‘ can we measure inflation expectations using twitter? ’. m. accornero and m. moscatelli in ‘ listening to the buzz : social media sentiment and retail depositors ’ trust ’, a measure of retail depositors ’ trust by checking twitter comments. banca d ’ italia, temi di discussione ( working papers ), 1165 ( 2018 ). social media are also used to assess customers ’ sentiment towards specific companies and its effect on stock returns, volatility and trading volumes. 6 twitter and news are used to measure economic policy uncertainty and to focus on payment card scams, to then relate them to trends in consumer payments. another strand of research uses data from single online real estate ads extracted from the web to understand the microstructure of the italian real estate market. 7 let me conclude by thanking once again all the speakers, discussants, panelists and participants for being here. i look forward to

simply that capital adequacy and leverage are two different concepts, and measure different things. the risk - based capital framework is not ideal for placing an absolute constraint on leverage, just as a leverage ratio is not ideal for assessing whether capital is adequate to cover the risks undertaken. this is why basel iii adopts a “ belt and braces ” approach, using the leverage ratio as an important backstop for the risk - based capital adequacy regime. returning to the rationale for using internal models to measure risk, it is important to remember that a key premise was that banks ’ risk - based capital ratios should consistently reflect banks ’ risk - taking. that was why basel ii provided not only for the use of internal models in pillar 1 of the regulatory framework, but also for the pillar 2 and 3 requirements so as to provide a second view on banks ’ solvency ( pillar 2 ), including one based on stress tests and performance measurement, and to facilitate market discipline via disclosure ( pillar 3 ). unfortunately, the financial crisis and subsequent analysis have shown that bank and supervisory practices are not as consistent as they could be. for example, the risk weights of some banks that introduced internal models under basel ii have been trending downwards in recent years, when experience and intuition say they should have been moving in the opposite direction. many people worried that basel ii would be procyclical. it would seem that those fears are largely unfounded, but for reasons that may be far from satisfactory! increasingly, this has led to questions about the credibility of internal model - based capital ratios. therefore, alongside the assessment of national regulations, the rcap has also started studying the consistency of outcomes at individual banks. as with the introduction of a rigorous peer review programme, the significance of this initiative should not be underestimated. never before have we had international teams of supervisors looking at the modelling practices at individual international banks. i think this is a quite telling example of the regulatory community ’ s commitment to improving the consistency, comparability and reliability of bank capital ratios. the basel committee ’ s two recently published studies on rwa variability have compared banks ’ estimates of risk - weighted assets on hypothetical portfolios of financial instruments ( for the trading book ) and credit counterparties ( for the banking book ). to give you an idea of the size of the task, in the case of the banking book, for example, the committee collected banks ’ probability of default ( pd ) and loss - given