{"title":"Taking the hunch out of the crunch: A framework to improve variable selection in models to detect financial statement fraud","authors":"Adrian Gepp, Kuldeep Kumar, Sukanto Bhattacharya","doi":"10.1111/acfi.13192","DOIUrl":null,"url":null,"abstract":"Abstract Financial statement fraud is a costly problem for society. Detection models can help, but a framework to guide variable selection for such models is lacking. A novel Fraud Detection Triangle (FDT) framework is proposed specifically for this purpose. Extending the well‐known Fraud Triangle, the FDT framework can facilitate improved detection models. Using Benford's law, we demonstrate the posited framework's utility in aiding variable selection via the element of surprise evoked by suspicious information latent in the data. We call for more research into variables that measure rationalisations for fraud and suspicious phenomena arising as unintended consequences of financial statement fraud.","PeriodicalId":47973,"journal":{"name":"Accounting and Finance","volume":"7 1","pages":"0"},"PeriodicalIF":3.1000,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounting and Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/acfi.13192","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract Financial statement fraud is a costly problem for society. Detection models can help, but a framework to guide variable selection for such models is lacking. A novel Fraud Detection Triangle (FDT) framework is proposed specifically for this purpose. Extending the well‐known Fraud Triangle, the FDT framework can facilitate improved detection models. Using Benford's law, we demonstrate the posited framework's utility in aiding variable selection via the element of surprise evoked by suspicious information latent in the data. We call for more research into variables that measure rationalisations for fraud and suspicious phenomena arising as unintended consequences of financial statement fraud.
期刊介绍:
Accounting & Finance enjoys an excellent reputation as an academic journal that publishes articles addressing significant research questions from a broad range of perspectives. The journal: • publishes significant contributions to the accounting, finance, business information systems and related disciplines • develops, tests, or advances accounting, finance and information systems theory, research and practice • publishes theoretical, empirical and experimental papers that significantly contribute to the disciplines of accounting and finance • publishes articles using a wide range of research methods including statistical analysis, analytical work, case studies, field research and historical analysis • applies economic, organizational and other theories to accounting and finance phenomena and publishes occasional special issues on themes such as on research methods in management accounting. Accounting & Finance is essential reading for academics, graduate students and all those interested in research in accounting and finance. The journal is also widely read by practitioners in accounting, corporate finance, investments, and merchant and investment banking.