{"title":"A theoretical study on the impediments of artificial intelligence in banking industry","authors":"Shweta Solanki, Meera Mathur","doi":"10.26524/jms.12.35","DOIUrl":null,"url":null,"abstract":"In recent years technology has become pertinent element of success for businesses and manufacturing industries. Technologies have also changed the ways in which the organizations perform their businesses. Artificial intelligence has become the buzz word in the field of technology in the recent scenario with enormous power to transform the traditional methods & to bring wide range of benefits. This technological innovation is gaining all the attraction of corporate world also has become the key issues of any nation’s strategy. Due to rapid rise in digitization and online banking, there is growing need to adopt & implement Artificial Intelligence technology in banking organizations too. AI has become important disruptor for banking industry. AI substantially reduces operating cost, increases efficiency & improves customer satisfaction. As the use of technology increases, it also brings numerous risks & challenges along with legal & governance issues. Machines decisions are going to replace human decisions,but how reliable, ethical & logical these decisions stay, becomes the question of everyone’s mind. Numbers of barrier are present for this technological driven innovation of AI. The study aims to focus on the challenges that banking organizations are experiencing. Banks are encountering all the hurdles starting from AI adoption to reluctance of customers for acceptance of AI driven decisions.","PeriodicalId":37730,"journal":{"name":"Journal of Management Information and Decision Science","volume":"58 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Management Information and Decision Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26524/jms.12.35","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Decision Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
In recent years technology has become pertinent element of success for businesses and manufacturing industries. Technologies have also changed the ways in which the organizations perform their businesses. Artificial intelligence has become the buzz word in the field of technology in the recent scenario with enormous power to transform the traditional methods & to bring wide range of benefits. This technological innovation is gaining all the attraction of corporate world also has become the key issues of any nation’s strategy. Due to rapid rise in digitization and online banking, there is growing need to adopt & implement Artificial Intelligence technology in banking organizations too. AI has become important disruptor for banking industry. AI substantially reduces operating cost, increases efficiency & improves customer satisfaction. As the use of technology increases, it also brings numerous risks & challenges along with legal & governance issues. Machines decisions are going to replace human decisions,but how reliable, ethical & logical these decisions stay, becomes the question of everyone’s mind. Numbers of barrier are present for this technological driven innovation of AI. The study aims to focus on the challenges that banking organizations are experiencing. Banks are encountering all the hurdles starting from AI adoption to reluctance of customers for acceptance of AI driven decisions.
期刊介绍:
Journal of Management Information and Decision Sciences (JMIDS) is a reputed open access journal affiliated to Allied Business Academies. The journal focuses on disseminating the latest research in the field of management information system and its role in decision making, as well their relationships to cognate disciplines including Economics, Finance, Management, Management Science, Marketing, Statistics, Operations Research and Engineering. The journal adheres to stringent double blind peer review policy to maintain the publication quality.