harnessing big data & machine learning technologies for central banks closing remarks by the deputy governor of the bank of italy luigi federico signorini rome, 27 march 2018 ladies and gentlemen, this two - day workshop on ‘ harnessing big data & machine learning technologies for central banks ’ is now drawing to a close. let me begin by thanking all the speakers, discussants and participants who have contributed to the success of this initiative. i have the pleasure of sharing with you some thoughts on the main issues. the papers presented during this two - day workshop have left no doubt as to the actual and potential value of big data and their importance for economic analysis. the present wave of data warehousing and business analytics confirms this, with big data poised to deliver topline research and statistical applications in a cost - effective way. huge amounts of data can provide substantial insights for the private and public sectors, enabling them to transform these data into new products and services for customers and citizens. big data are already changing some aspects of business in the financial industry with regard to banks, hedge funds, broker - dealers, and other firms. central banks and supervisors are also interested. the widespread adoption of digital technology has increased the number and depth of information sources of interest to economic analysis and financial stability, two of the core concerns of financial authorities. we are not only voracious data users, we are also big data producers. we collect terabytes of granular data in the fields of banking supervision, oversight of financial markets and payment systems. central banks can and should harvest the benefits of new technologies. we should select the best technology and exploit its power in turning ideas into actual applications and improved statistical and computing efficiency. the potential is huge, but there are, as usual, pros and cons. there are important trade - offs that must be kept in mind. i see two main issues, or rather groups of issues. one is technical, and some papers in this workshop have pointed to it. we need to keep analysing and experimenting in order to be able to assess the real information value of big data bases. ‘ n = all ’, as in the popular definition by mayer - schonberger and cukier 1, may sometimes be illusory. sometimes big data turn out not to be representative of the whole population. for example, groves ( 2016 ) 2 argues that big data often contain few variables and extracting their value requires linkages to other data ; furthermore, they lack representative

advanced liquidity management facility ; bis central bankers ’ speeches extensible markup language ( xml ) / iso 20022 / swift compatible based messaging system conforming to international standards ; and real time information and transaction monitoring and control system. conclusion to summarise, indian banks have traversed a long way in their journey to provide efficient, customer centric services. banks have to adapt to greater regulation, competition and consolidation as also meet increasingly diverse and demanding customer expectations. in such a scenario, adoption of information technology and cbs in particular has been immensely useful in the progress made, so far. but, there is need to look beyond cbs for leveraging technology for still better and efficient growth. while the advent of state - of - the - art technologies and global best practices undoubtedly offer improved agility, efficiency, and faster implementation cycles, banks need to be mindful of the challenges associated with deployment of it. these challenges, once understood and mitigated properly, are perfectly manageable. the times to come will require much more professional and sophisticated it leadership with vision than ever before. as history indicates, successful banks are those that have understood the potential of new technologies and aligned themselves to fully leveraging its power. these are banks that have focused on the adaptive change that made the technology transformation process successful. while talking of challenges, one of the challenges that the entire banking industry and service providers will increasingly face is the ability to provide required services to customers in an uninterrupted manner in normal times, and more so while facing adverse circumstances like catastrophes, sabotage, war, riots, power supply failures, endemics etc. extensive use of technology has also lead to significantly increased infrastructure sharing and interdependence. moreover, since financial markets are in a state of high integration, problems in one segment like payment and settlements can lead to severe impact in several other areas, particularly if some problems occur at some significant market participant / service provider ’ s end. business continuity management and disaster recovery preparations, therefore, need to be given high importance. gone are the days when bcp and dr were generally documented, but not effectively monitored and dr was understood to be limited to data backup arrangements. recently, there was an incident where a large number of customers in a large bank had to face inconvenience as the working of the bank was impacted for considerable time due to technical issues. it is possible that something important might have been missed out in the planning, implementation or testing of bcp