BIS Examines Use of Big Data and Machine Learning at Central Banks
BIS published a paper that provides an overview on the use of big data and machine learning in the central bank community. The paper leverages on a survey conducted in 2020 with responses from 52 central banks worldwide. The paper examines how central banks define and use big data, as well as which opportunities and challenges they see. Institutions use big data and machine learning for economic research, in the areas of financial stability and monetary policy, as well as for suptech and regtech applications. Data quality, sampling, and representativeness are major challenges for central banks and so is legal uncertainty around data privacy and confidentiality. The paper notes that cooperation among public authorities could improve central banks’ ability to collect, store, and analyze big data.
Among other challenges, several institutions report constraints in setting up an adequate IT infrastructure and in developing the necessary human capital. Overall, the analysis highlights that central banks define big data in an encompassing way that includes unstructured non-traditional as well as structured data sets. Central banks' interest in big data and machine learning has markedly increased over the last years. In 2020, over 80% of central banks report that they use big data, up from just 30% five years ago. Among the institutions that currently use big data, over 70% use it for economic research, while 40% state that they use it to inform policy decisions. These numbers suggest that big data and machine learning offer many useful applications and can help central banks in fulfilling their mandate. The vast majority of central banks are now conducting projects that involve big data and the central banks are willing to join forces to reap the benefits of big data. Indeed, half of them reported an interest in collaborating in one or more specific project, with three types of cooperation envisaged:
- By sharing knowledge among those institutions that have developed specific expertise that can be reused in other jurisdictions. These expertise include general big data techniques (for example, data visualization, network analysis, machine learning tools), more general information management issues (for example, development of open-source coding, data-sharing protocols, encryption and anonymization techniques for using confidential data) as well as specific applications that are more devoted to the central bank community (for example, suptech and regtech areas).
- By using big data to work on global issues such as international spillovers, global value chains, and cross-border payments.
- By developing joint exploratory projects to benefit from economies of scale and collectively share (limited) financial and human resources.
International financial institutions can greatly support these cooperative approaches. They can facilitate innovation by promoting technological solutions to harmonize data standards and processes among jurisdictions. With this spirit, the BIS Innovation Hub has been established to identify and develop insights into critical trends in financial technology of relevance to central banks, explore the development of public goods to enhance the functioning of the global financial system, and serve as a focal point for a network of central bank experts on innovation. Such a network could undoubtedly play an important role in facilitating international cooperation to exploit big data sources and techniques.
Related Links
Keywords: International, Banking, Big Data, Regtech, Suptech, Machine Learning, BIS
Previous Article
BCB Establishes Committee to Oversee Regulatory Sandbox OperationsRelated Articles
US Agencies Issue Several Regulatory and Reporting Updates
The Board of Governors of the Federal Reserve System (FED) adopted the final rule on Adjustable Interest Rate (LIBOR) Act.
ECB Issues Multiple Reports and Regulatory Updates for Banks
The European Central Bank (ECB) published an updated list of supervised entities, a report on the supervision of less significant institutions (LSIs), a statement on macro-prudential policy.
HKMA Keeps List of D-SIBs Unchanged, Makes Other Announcements
The Hong Kong Monetary Authority (HKMA) published a circular on the prudential treatment of crypto-asset exposures, an update on the status of transition to new interest rate benchmarks.
EU Issues FAQs on Taxonomy Regulation, Rules Under CRD, FICOD and SFDR
The European Commission (EC) adopted the standards addressing supervisory reporting of risk concentrations and intra-group transactions, benchmarking of internal approaches, and authorization of credit institutions.
CBIRC Revises Measures on Corporate Governance Supervision
The China Banking and Insurance Regulatory Commission (CBIRC) issued rules to manage the risk of off-balance sheet business of commercial banks and rules on corporate governance of financial institutions.
HKMA Publications Address Sustainability Issues in Financial Sector
The Hong Kong Monetary Authority (HKMA) made announcements to address sustainability issues in the financial sector.
EBA Updates Address Basel and NPL Requirements for Banks
The European Banking Authority (EBA) published regulatory standards on identification of a group of connected clients (GCC) as well as updated the lists of identified financial conglomerates.
ESMA Publishes 2022 ESEF XBRL Taxonomy and Conformance Suite
The General Board of the European Systemic Risk Board (ESRB), at its December meeting, issued an updated risk assessment via the quarterly risk dashboard and held discussions on key policy priorities to address the systemic risks in the European Union.
FCA Sets up ESG Committee, Imposes Penalties, and Issues Other Updates
The Financial Conduct Authority (FCA) is seeking comments, until December 21, 2022, on the draft guidance for firms to support existing mortgage borrowers.
FSB Reports Assess NBFI Sector and Progress on LIBOR Transition
The Financial Stability Board (FSB) published a report that assesses progress on the transition from the Interbank Offered Rates, or IBORs, to overnight risk-free rates as well as a report that assesses global trends in the non-bank financial intermediation (NBFI) sector.