The use of big data analytics and artificial intelligence in central banking

Committee, Irving Fisher

The use of big data analytics and artificial intelligence in central banking

Irving Fisher Committee

No 50 in IFC Bulletins from Bank for International Settlements

Date: 2019 Written 2019-05
ISBN: 978-92-9259-262-2
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http://www.bis.org/ifc/publ/ifcb50.htm (text/html)

Chapters in this book:

A personal view on big data and policymaking: Naruki Mori
A robust machine learning approach for credit risk analysis of large loan-level datasets using deep learning and extreme gradient boosting: Anastasios Petropoulos, Vasilis Siakoulis, Evaggelos Stavroulakis and Aristotelis Klamargias
Annex – presentations: Sanjiv Das
Big data and FinRisk: Sanjiv Das
Big data for central bank policies: Yati Kurniati
Big data for central banks: Bruno Tissot
Big data: new insights for economic policy: Gabriel Quirós-Romero
Big data: new insights for economic policy – The Bank of England experience: Paul Robinson
Building pathways for policy making with big data: Claudia Buch
Building pathways for policy making with big data: Erwin Rijanto
Data science at the Netherlands Bank: Iman Lelyveld
Exploiting big data for sharpening financial sector risk assessment: Kimmo Soramäki
Exploring big data to sharpen financial sector risk assessment: David Roi Hardoon
Google econometrics: nowcasting euro area car sales and big data quality requirements: Per Nymand-Andersen and Emmanouil Pantelidis
How do central banks use big data to craft policy?: Per Nymand-Andersen
How do central banks use big data to craft policy?: Bruno Tissot
Introduction to network science & visualisation: Kimmo Soramäki
Introduction to text mining: Stephen Hansen
Machine Learning: Classification and Clustering: Sanjiv Das
Measuring market and consumer sentiment and confidence: Stephen Hansen
Measuring stakeholders’ expectations for the central bank’s policy rate: Alvin Andhika Zulen and Okiriza Wibisono
Nowcasting New Zealand GDP using machine learning algorithms: Adam Richardson, Thomas van Florenstein Mulder and Tugrul Vehbi
Nowcasting private consumption: traditional indicators, uncertainty measures, credit cards and some internet data: María Gil, Javier Pérez and Alberto Urtasun
Predictability in sovereign bond returns using technical trading rule: do developed and emerging markets differ?: Tom Fong and Gabriel Wu
Promise: measuring from inflation to discrimination: Roberto Rigobon
Standardised approach in developing economic indicators using internet searching applications: Paphatsorn Sawaengsuksant
The Bank of France datalake: Renaud Lacroix
The framework of big data: a microdata strategy: Robert Kirchner
The use of big data analytics and artificial intelligence in central banking – An overview: Okiriza Wibisono, Hidayah Dhini Ari, Anggraini Widjanarti, Alvin Andhika Zulen and Bruno Tissot
Understanding big data: fundamental concepts and framework: Paul Robinson

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