Explainable artificial intelligence (XAI): A systematic literature review on taxonomies and applications in finance
Main Author: | |
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Publication Date: | 2024 |
Other Authors: | , , |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/10071/31145 |
Summary: | Explainable Artificial Intelligence (XAI) is a growing area of research that aims to improve the interpretability of the not-so-informative black-box models. However, it is currently difficult to categorize an existing method in terms of its intrinsic characteristics and explainability. We provide a new unified yet simple taxonomy for the categorization of XAI methods and present the explainability methods currently being applied in finance applications. For both purposes, we present two separate systematic literature reviews: an anthological search for surveys on XAI methods in order to present a unified taxonomy, followed by an exposition of the XAI methods currently in use that have been found. We also concisely define the existing explainability methods using the proposed categories based on the ones most commonly addressed in the reviewed literature and pinpoint specific XAI methods being used in practical applications in Finance. |
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Explainable artificial intelligence (XAI): A systematic literature review on taxonomies and applications in financeAIArtificial intelligenceFinancial applicationsExplainable machine learningSystematic literature reviewXAIExplainable Artificial Intelligence (XAI) is a growing area of research that aims to improve the interpretability of the not-so-informative black-box models. However, it is currently difficult to categorize an existing method in terms of its intrinsic characteristics and explainability. We provide a new unified yet simple taxonomy for the categorization of XAI methods and present the explainability methods currently being applied in finance applications. For both purposes, we present two separate systematic literature reviews: an anthological search for surveys on XAI methods in order to present a unified taxonomy, followed by an exposition of the XAI methods currently in use that have been found. We also concisely define the existing explainability methods using the proposed categories based on the ones most commonly addressed in the reviewed literature and pinpoint specific XAI methods being used in practical applications in Finance.IEEE2024-02-21T15:41:55Z2024-01-01T00:00:00Z20242024-02-21T15:33:15Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/31145eng2169-353610.1109/ACCESS.2023.3347028Martins, T.de Almeida, A.Cardoso, E.Nunes, L.info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-07-07T03:28:31Zoai:repositorio.iscte-iul.pt:10071/31145Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T18:24:39.526585Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Explainable artificial intelligence (XAI): A systematic literature review on taxonomies and applications in finance |
title |
Explainable artificial intelligence (XAI): A systematic literature review on taxonomies and applications in finance |
spellingShingle |
Explainable artificial intelligence (XAI): A systematic literature review on taxonomies and applications in finance Martins, T. AI Artificial intelligence Financial applications Explainable machine learning Systematic literature review XAI |
title_short |
Explainable artificial intelligence (XAI): A systematic literature review on taxonomies and applications in finance |
title_full |
Explainable artificial intelligence (XAI): A systematic literature review on taxonomies and applications in finance |
title_fullStr |
Explainable artificial intelligence (XAI): A systematic literature review on taxonomies and applications in finance |
title_full_unstemmed |
Explainable artificial intelligence (XAI): A systematic literature review on taxonomies and applications in finance |
title_sort |
Explainable artificial intelligence (XAI): A systematic literature review on taxonomies and applications in finance |
author |
Martins, T. |
author_facet |
Martins, T. de Almeida, A. Cardoso, E. Nunes, L. |
author_role |
author |
author2 |
de Almeida, A. Cardoso, E. Nunes, L. |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Martins, T. de Almeida, A. Cardoso, E. Nunes, L. |
dc.subject.por.fl_str_mv |
AI Artificial intelligence Financial applications Explainable machine learning Systematic literature review XAI |
topic |
AI Artificial intelligence Financial applications Explainable machine learning Systematic literature review XAI |
description |
Explainable Artificial Intelligence (XAI) is a growing area of research that aims to improve the interpretability of the not-so-informative black-box models. However, it is currently difficult to categorize an existing method in terms of its intrinsic characteristics and explainability. We provide a new unified yet simple taxonomy for the categorization of XAI methods and present the explainability methods currently being applied in finance applications. For both purposes, we present two separate systematic literature reviews: an anthological search for surveys on XAI methods in order to present a unified taxonomy, followed by an exposition of the XAI methods currently in use that have been found. We also concisely define the existing explainability methods using the proposed categories based on the ones most commonly addressed in the reviewed literature and pinpoint specific XAI methods being used in practical applications in Finance. |
publishDate |
2024 |
dc.date.none.fl_str_mv |
2024-02-21T15:41:55Z 2024-01-01T00:00:00Z 2024 2024-02-21T15:33:15Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/31145 |
url |
http://hdl.handle.net/10071/31145 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2169-3536 10.1109/ACCESS.2023.3347028 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
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openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
IEEE |
publisher.none.fl_str_mv |
IEEE |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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