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2.
Big Data Analytics and Engineering for Medicare Fraud Detection
by Herland, Matthew Andrew, Ph.D.  Florida Atlantic University. 2019: 205 pages; 13814186.
3.
Modernizing Check Fraud Detection with Machine Learning
by Rose, Lydia M., M.S.  Utica College. 2018: 64 pages; 13421455.
4.
Mitigating corporate financial fraud: A qualitative study
by Bejarano, Johnnie Ray, D.B.A.  University of Phoenix. 2008: 269 pages; 3338359.
5.
More than just good deeds: Fraud within religious organizations
by Peters, Carrol Susan, M.S.  Utica College. 2015: 62 pages; 1599154.
6.
Ratio of Income Tax Expense to Operating Income as an Indicator of Fraud
by Killen, Karen L., Ph.D.  Northcentral University. 2016: 119 pages; 10105357.
7.
Dynamic Fraud Detection via Sequential Modeling
by Zheng, Panpan, Ph.D.  University of Arkansas. 2020: 140 pages; 27960392.
8.
Machine-Learning Methods for Credit Card Fraud Detection
by Woolston, Sarah E., M.S.  California State University, Long Beach. 2017: 100 pages; 10602012.
9.
Narrowing the Gap of Financial Fraud Detection in Corporations
by Aborbie, Solomon, D.B.A.  Walden University. 2015: 140 pages; 3688003.
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Fraud Prevention and Employee Rationalization in New York State Public Schools
by Slezak, Kathleen, Ph.D.  State University of New York at Albany. 2013: 151 pages; 3611898.
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Indicators of management fraud in community banks
by McAteer, Michael J., D.B.A.  University of Phoenix. 2008: 276 pages; 3339939.
20.
A Comparative Case Study of Internal Controls and the Impact of Fraud on Nonprofit Organizations
by Buabeng, Albert Asiedu, D.B.A.  Northcentral University. 2020: 181 pages; 28091358.
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Three essays on corporate governance
by Marshall, Cassandra D., Ph.D.  Indiana University. 2011: 150 pages; 3491494.
24.
Reducing the Frequency and Effects of Fraudulent Activities in Community Action Agencies
by Blye, Marvin L. J., D.B.A.  Walden University. 2020: 146 pages; 28151060.
26.
Mine detection rats: Effects of repeated extinction on detection rates
by Mahoney, Amanda M., Ph.D.  Western Michigan University. 2012: 67 pages; 3531894.
27.
An Examination of User Detection of Business eMail Compromise amongst Corporate Professionals
by Aviv, Shahar Sean, Ph.D.  Nova Southeastern University. 2019: 141 pages; 27667282.
28.
A Predictive Modeling for Detecting Fraudulent Automobile Insurance Claims
by Pu, Yuan, M.S.  California State University, Long Beach. 2019: 44 pages; 13900194.
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