the bank of italy sponsored a hackathon, a worldwide competition on applying big data, natural language processing and artificial intelligence techniques to green and sustainable finance, that was jointly organized with the bis innovation hub of singapore under the italian g20 presidency. in 2020, we created milano hub, a technological hub supporting the development of innovation and the digital transformation of the italian financial system. after the great success of the first two calls for proposals, we will launch a third one in the next months in the last few years, we have redesigned our recruitment and hiring process by seeking out new skillsets such as big data, machine learning and artificial intelligence. this is just the beginning. we need to rethink our processes and foster the adoption and development of the right skills. to achieve these goals, we have sponsored special data science training programmes in some italian universities. the new cohort of hires have already started their journey, which aims to create a flatter organizational structure. in 2020, the total amount of data created, captured, copied, and consumed globally was around 100 zettabytes ( an astounding value of 1023 bytes ), and it is expected to rapidly increase, reaching 180 zettabytes in 2025. 1 the mind - boggling amount of data that is now available to us, provided we are able to analyse it effectively, can give us a better picture of the economy at both the micro and the macro level. the bank of italy has constantly striven to be at the cutting edge in developing software and hardware platforms, enabling big data analytics2 for statistical and economic applications. one of the most significant takeaways from this workshop is recognizing that data is not just a resource : it is essential for effective decision - making in central banking. the quality, quantity, and timeliness of data can make all the difference in crafting policies that safeguard our economies and maintain financial stability. by harnessing the power of data science, central banks can enhance their capabilities, anticipate trends, and respond swiftly to emerging challenges. data taken from https : / / www. statista. com / statistics / 871513 / worldwide - data - created / on september 25 2023. see, for example, ‘ big data processing : is there a framework suitable for economists and statisticians? ’, 2017 ieee international conference on big data ( big data ), 2017, pp. 2804 - 2811, doi : 10. 1109 / bigdata

a possible solution for processing individual data. 4 the bank of italy has begun experimenting with these technologies. see'calibrating noise to sensitivity in private data analysis ’, cynthia dwork frank mcsherry, kobbi nissim, 2006. see ‘ a fully homomorphic encryption scheme ’, craig gentry, 2009. it is important to note that there is no one - size - fits - all approach to data ethics. the specific ethical considerations will vary depending on the type of data being collected and used, the purpose for which it is being used, and the potential impact on individuals and society. looking ahead as we are nearing the conclusion of this workshop, let us bear in mind that our journey with data science in central banking has just begun. the knowledge and skills we have acquired here are tools that we can wield to drive innovation and excellence in our institutions. it is our responsibility to apply what we ’ ve learned, adapt to the everevolving landscape of technology and data, and lead the way in shaping the future of central banking. i encourage all of you to stay connected, collaborate, and continue the dialogue beyond this workshop. the relationships we have built here can be the foundation for future partnerships and collaborations that will drive progress in our field. the bank of italy is firmly committed to carrying out further research on these issues and cooperating with other institutions to strengthen methodologies and applications. finally, let us not forget the significance of our work. central banking plays a key role in the stability and prosperity of our countries. data science can help us navigate the complex waters of modern finance. together, we can steer our institutions toward greater resilience, transparency, and effectiveness. we have had the privilege of learning from distinguished experts and practitioners in the field, who have shared their knowledge, experiences, and insights. these interactions have enriched our perspectives and deepened our understanding of the intricate relationship between data science and central banking. i would like to extend my heartfelt gratitude to all the speakers, instructors, and organizers who have made this workshop a resounding success. thank you all for your dedication, your commitment, and your thirst for knowledge. it has been an honour and a privilege for me to be a part of this workshop with you. i wish you all continued success in your endeavours, and may the insights gained here guide us toward a brighter future in our profession.