Data Science Opportunities at Central Banks: Overview

Dmytro Krukovets

Visnyk of the National Bank of Ukraine, 2020, issue 249, 13-24

Abstract: This paper reviews the main streams of Data Science algorithm usage at central banks and shows their rising popularity over time. It contains an overview of use cases for macroeconomic and financial forecasting, text analysis (newspapers, social networks, and various types of reports), and other techniques based on or connected to large amounts of data. The author also pays attention to the recent achievements of the National Bank of Ukraine in this area. This study contributes to the building of the vector for research the role of Data Science for central banking.

Keywords: forecasting; Machine Learning; Data Science; Natural-Language Processing; macroeconomics (search for similar items in EconPapers)
JEL-codes: C45 C53 C82 E27 E37 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:ukb:journl:y:2020:i:249:p:13-24

DOI: 10.26531/vnbu2020.249.02

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