Machine learning in central banking

Committee, Irving Fisher

Machine learning in central banking

Irving Fisher Committee

No 57 in IFC Bulletins from Bank for International Settlements

Date: 2022 Written 2022-11
ISBN: 978-92-9259-607-1
References: View references in EconPapers View complete reference list from CitEc
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http://www.bis.org/ifc/publ/ifcb57.htm (text/html)

Chapters in this book:

A novel machine learning-based validation workflow for financial market time series: Magdalena Erdem and Taejin Park
An artificial intelligence application for accounting data cleansing: Pablo Jiménez and Tello Serrano
Anomaly detection methods and tools for big data: Shir Kamenetsky Yadan
Applications of variational inference in the Bank of Russia: Sergei Seleznev and Ramis Khabibullin
Classifying payment patterns with artificial neural networks: an autoencoder approach: Luis Gerardo Gage, Raúl Morales-Resendiz, John Arroyo, Jeniffer Rubio and Paolo Barucca
Cloud computing research collaboration:an application to access to cash and financial services: Danielle V Handel, Anson Ho, Kim Huynh, David T Jacho-Chavez and Carson Rea
Data science opportunities with non-cash transactional payments: Per Nymand-Andersen
Deep learning solutions for dynamic stochastic general equilibrium models: Mo Ashtari and Vladimir Skavysh
Disagreement between human and machine predictions: Daisuke Miyakawa and Kohei Shintani
Estimating the effect of central bank independence on inflation using longitudinal targeted maximum likelihood estimation: Philipp Baumann, Enzo Rossi and Michael Schomaker
Fostering European SMEs' internationalization using big data: the BIZMAP application: Jean-Noel Kien, Etienne Kintzler and Theo Nicolas
Getting insight of employment vulnerability from online news: a case study in Indonesia: Nursidik Heru Praptono and Alvin Andhika Zulen
Machine learning applications in central banking: an overview: Douglas Araujo, Giuseppe Bruno, Juri Marcucci, Rafael Schmidt and Bruno Tissot
Machine learning for anomaly detection in datasets with categorical variables and skewed distributions: Matteo Accornero and Gianluca Boscariol
Machine learning for anomaly detection in financial regulatory data: Maryam Haghighi, Colin Jones and James Younker
Machine learning real-time CPI forecasting: Mariam Mamedeli
Machine learning-based approaches for automatic data validation and outlier control of loan microdata in the Bank of Russia: Dimitrii Diachkov
Monetary economics and communication: new data, new tools,new and old questions: Michael McMahon
Monitoring at scale: Enrico Apicella, Marco D'Errico, Pedro Marques, Antonio Ciullo and Caroline Übelhör
Novel methodologies for data quality management Anomaly detection in the Portuguese central credit register: André Faria da Costa, Francisco Fonseca and Susana Maurício
Opening Remarks: Piero Cipollone
Predicting foreign investors' behavior and flows projection in Indonesia government bonds market using machine learning: Anggraini Widjanarti, Arinda Dwi Okfantia and Muhammad Abdul Jabbar
Probability of default model with transactional data of Russian companies: Gleb Buzanov and Andrey Shevelev
Restoration of omissions in the quarterly indicators of financial statements for the other financial institutions in the Bank of Russia: Anna Borisenko, Denis Koshelev, Petr Milyutin and Alieva Piruza
Supervised machine learning for estimating the institutional sectors of legal entities on a large scale: Francesca Benevolo, Thomas Gottron, Ilaria Febbo and Nicolò Pegoraro
Supervisory letter writing app: expediting letter drafting and ensuring tone consistency: Joshua Tan, Chi Ken Shum and Mohd Akmal Amri
Text data analysis using Latent Dirichlet Allocation: an application to FOMC transcripts: Hector Carcel
The impairment costs of traditional non-quantitative retail banking practices during residential real estate foreclosure sales and their effect on National, Central & Reserve bank(s) policy: Emmanuel Blonkowski and James N Nicol
The use of AI for company data gathering Finding and monitoring fintechs in Germany and France: Elisabeth Devys and Ulf von Kalckreuth
Time series outlier detection, a data-driven approach: Nicola Benatti and Alexis Maurin
Unsupervised outlier detection in official statistics: Nhan-Tam Nguyen
Using deep learning technique to automate banknote defect classification: Jiradett Kerdsri and Pucktada Treeratpituk
Using news sentiment for economic forecasting: a Malaysian case study: Eilyn Chong, Chiung Ching Ho, Zhong Fei Ong and Hong H Ong
Using twitter data to measure inflation perception: Julien Denes, Ariane Lestrade and Lou Richardet

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