Data‐driven auditing: A predictive modeling approach to fraud detection and classification-Reference-Cited by-同舟云学术

Data‐driven auditing: A predictive modeling approach to fraud detection and classification

Published:2019-07 Issue:3 Volume:30 Page:64-82
ISSN:1044-8136
Container-title:Journal of Corporate Accounting & Finance
language:en
Short-container-title:J. Corp. Acct. Fin

Author:

Singh Nitin¹,Lai Kee‐hung²,Vejvar Markus²,Cheng T. C. Edwin²

Affiliation:

1. Department of Operations ManagementIndia Institute of Management Kashipur India

2. Department of Logistics and Maritime StudiesFaculty of Business, The Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong

Publisher

Wiley

Subject

General Economics, Econometrics and Finance,Accounting

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcaf.22389

Reference110 articles.

1. ACFE. (2016).Report to the nation: Occupational fraud and abuse. Available athttp://www.acfe.com/rttn2016.aspx

2. Agency Theory and the Internal Audit

3. Alles M. &Gray G. L.(2015). The pros and cons of using big data in auditing: A synthesis of the literature and a research agenda.Proceedings of the 9th Biennial Research Symposium. Toronto Ontario: Canada

4. Auditor Independence Revisited

5. Benchmarking state-of-the-art classification algorithms for credit scoring

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