{"title":"可解释人工智能 (xAI) 在金融领域的应用进展","authors":"Tony Klein, Thomas Walther","doi":"10.1016/j.frl.2024.106358","DOIUrl":null,"url":null,"abstract":"Explainable Artificial Intelligence addresses the black box problem associated with AI, aiming to promote greater transparency, traceability, and trust in applications of AI. xAI is becoming a vital element in finance and economics in fields like risk management, credit decisions, and regulatory compliance. The need for xAI arises from the challenges in understanding, trusting, and communicating AI-generated results. While some argue for the adoption of inherently interpretable models, others critique popular xAI methods. This special issue explores xAI’s role in finance and its advances, focusing on its implications for future research, practice, and policy in FinTech.","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"18 1","pages":""},"PeriodicalIF":7.4000,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Advances in Explainable Artificial Intelligence (xAI) in Finance\",\"authors\":\"Tony Klein, Thomas Walther\",\"doi\":\"10.1016/j.frl.2024.106358\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Explainable Artificial Intelligence addresses the black box problem associated with AI, aiming to promote greater transparency, traceability, and trust in applications of AI. xAI is becoming a vital element in finance and economics in fields like risk management, credit decisions, and regulatory compliance. The need for xAI arises from the challenges in understanding, trusting, and communicating AI-generated results. While some argue for the adoption of inherently interpretable models, others critique popular xAI methods. This special issue explores xAI’s role in finance and its advances, focusing on its implications for future research, practice, and policy in FinTech.\",\"PeriodicalId\":12167,\"journal\":{\"name\":\"Finance Research Letters\",\"volume\":\"18 1\",\"pages\":\"\"},\"PeriodicalIF\":7.4000,\"publicationDate\":\"2024-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Finance Research Letters\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.1016/j.frl.2024.106358\",\"RegionNum\":2,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Finance Research Letters","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1016/j.frl.2024.106358","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Advances in Explainable Artificial Intelligence (xAI) in Finance
Explainable Artificial Intelligence addresses the black box problem associated with AI, aiming to promote greater transparency, traceability, and trust in applications of AI. xAI is becoming a vital element in finance and economics in fields like risk management, credit decisions, and regulatory compliance. The need for xAI arises from the challenges in understanding, trusting, and communicating AI-generated results. While some argue for the adoption of inherently interpretable models, others critique popular xAI methods. This special issue explores xAI’s role in finance and its advances, focusing on its implications for future research, practice, and policy in FinTech.
期刊介绍:
Finance Research Letters welcomes submissions across all areas of finance, aiming for rapid publication of significant new findings. The journal particularly encourages papers that provide insight into the replicability of established results, examine the cross-national applicability of previous findings, challenge existing methodologies, or demonstrate methodological contingencies.
Papers are invited in the following areas:
Actuarial studies
Alternative investments
Asset Pricing
Bankruptcy and liquidation
Banks and other Depository Institutions
Behavioral and experimental finance
Bibliometric and Scientometric studies of finance
Capital budgeting and corporate investment
Capital markets and accounting
Capital structure and payout policy
Commodities
Contagion, crises and interdependence
Corporate governance
Credit and fixed income markets and instruments
Derivatives
Emerging markets
Energy Finance and Energy Markets
Financial Econometrics
Financial History
Financial intermediation and money markets
Financial markets and marketplaces
Financial Mathematics and Econophysics
Financial Regulation and Law
Forecasting
Frontier market studies
International Finance
Market efficiency, event studies
Mergers, acquisitions and the market for corporate control
Micro Finance Institutions
Microstructure
Non-bank Financial Institutions
Personal Finance
Portfolio choice and investing
Real estate finance and investing
Risk
SME, Family and Entrepreneurial Finance