{"title":"Data analytics (ab) use in healthcare fraud audits","authors":"Jared Koreff , Martin Weisner , Steve G. Sutton","doi":"10.1016/j.accinf.2021.100523","DOIUrl":null,"url":null,"abstract":"<div><p>This study explores how government-adopted audit data analytic tools promote the abuse of power by auditors enabling politically sensitive processes that encourage industry-wide normalization of behavior. In an audit setting, we investigate how a governmental organization enables algorithmic decision-making to alter power relationships to effect organizational and industry-wide change. While prior research has identified discriminatory threats emanating from the deployment of algorithmic decision-making, the effects of algorithmic decision-making on inherently imbalanced power relationships have received scant attention. Our results provide empirical evidence of how systemic and episodic power relationships strengthen each other, thereby enabling the governmental organization to effect social change that might be too politically prohibitive to enact directly. Overall, the results suggest that there are potentially negative effects caused by the use of algorithmic decision-making and the resulting power shifts, and these effects create a different view of the level of purported success attained through auditor use of data analytics.</p></div>","PeriodicalId":47170,"journal":{"name":"International Journal of Accounting Information Systems","volume":"42 ","pages":"Article 100523"},"PeriodicalIF":4.1000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.accinf.2021.100523","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Accounting Information Systems","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1467089521000257","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 7
Abstract
This study explores how government-adopted audit data analytic tools promote the abuse of power by auditors enabling politically sensitive processes that encourage industry-wide normalization of behavior. In an audit setting, we investigate how a governmental organization enables algorithmic decision-making to alter power relationships to effect organizational and industry-wide change. While prior research has identified discriminatory threats emanating from the deployment of algorithmic decision-making, the effects of algorithmic decision-making on inherently imbalanced power relationships have received scant attention. Our results provide empirical evidence of how systemic and episodic power relationships strengthen each other, thereby enabling the governmental organization to effect social change that might be too politically prohibitive to enact directly. Overall, the results suggest that there are potentially negative effects caused by the use of algorithmic decision-making and the resulting power shifts, and these effects create a different view of the level of purported success attained through auditor use of data analytics.
期刊介绍:
The International Journal of Accounting Information Systems will publish thoughtful, well developed articles that examine the rapidly evolving relationship between accounting and information technology. Articles may range from empirical to analytical, from practice-based to the development of new techniques, but must be related to problems facing the integration of accounting and information technology. The journal will address (but will not limit itself to) the following specific issues: control and auditability of information systems; management of information technology; artificial intelligence research in accounting; development issues in accounting and information systems; human factors issues related to information technology; development of theories related to information technology; methodological issues in information technology research; information systems validation; human–computer interaction research in accounting information systems. The journal welcomes and encourages articles from both practitioners and academicians.