Data science and machine learning for a data-driven central bank

Giuseppe Bruno and Juri Marcucci

INTRODUCTION

In the book Brief Answers to the Big Questions by Stephen Hawking, published in October 2018, seven months after his death, the renowned theoretical physicist warned us by writing

It’s tempting to dismiss the notion of highly intelligent machines as mere science fiction, but this would be a mistake, and potentially our worst mistake ever.

The Banca d’Italia established a multidisciplinary team to address, in a timely and thorough manner, the potential benefits and hidden risks of embracing the technological challenges of artificial intelligence (AI) and machine learning (ML) fuelled by the advances in big data, which continues to evolve. This chapter provides a short but comprehensive (although by no means exhaustive) discussion of the steps the bank has taken to avoid succumbing to the temptation Hawking warns about.

In this analysis, we describe the most recent research and the new statistical applications developed at the Banca d’Italia using big data and ML, with the hope that our work offers some guidance for those who wish to start a similar journey in their company or institution.

The chapter is organised as follows. We first present a taxonomy

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