Bullion
Keywords
Artificial Intelligence, Machine Learning, Big Data, Public Policy
Abstract
In order to evaluate the status of the economy, policymakers and the private sector have relied on Statistics produced by official statistical institutes for decades. These data must be gathered with great effort, and publishing frequently takes months or years to complete. However, both the amount of data that is readily available and the tools and software used to analyse it have grown dramatically over the past few years. These changes have increased interest in big data and machine learning among central banks. The application of big data and machine learning in central banking is examined in this study. The bulk of central banks hold formal discussions about big data within their organisations. In many fields, such as research, monetary policy, and financial Stability, big data and machine learning applications are used. Furthermore, central banks report leveraging big data for regulation and monitoring (suptech and regtech applications). The legal uncertainty around data privacy and confidentiality is a major concern for central banks, as are issues with data quality, sampling, and representativeness. Several institutions report difficulties in building the necessary IT infrastructure and human capacity. Collaboration between government entities could improve central banks' capacity to gather, store, and analyse massive data.
Publication Title
Bullion (Central Bank of Nigeria)
Issue
47
Volume
Vol.47 NO.1
First Page
14
Last Page
27
Recommended Citation
Kingsley-Nsirim, Leticia Dr.
(2023)
"Big Data Analytics, Al and Machine Learning For Central Banks: What it Portends For Emerging Economies in Africa,"
Bullion: Vol. 47:
No.
1, Article 2.
Available at:
https://dc.cbn.gov.ng/bullion/vol47/iss1/2