Using neural networks to predict financial reporting fraud: Part 1

1999 ◽  
Vol 1999 (5) ◽  
pp. 14-17 ◽  
Author(s):  
Michael J. Cerullo ◽  
Virginia Cerullo
Keyword(s):  
Neural Networks ◽  
Financial Reporting ◽  
Financial Reporting Fraud

Financial Reporting Fraud: Public and Private Companies

2016 ◽  
Vol 1 (1) ◽  
pp. A27-A41 ◽  
Author(s):  
A. Scott Fleming ◽  
Dana R. Hermanson ◽  
Mary-Jo Kranacher ◽  
Richard A. Riley
Keyword(s):  
Financial Reporting ◽  
Primary Objective ◽  
Private Company ◽  
Private Companies ◽  
Public And Private ◽  
Public Companies ◽  
Multivariate Tests ◽  
Public Company ◽  
Public Versus Private ◽  
Financial Reporting Fraud

ABSTRACT This study uses survey data gathered by the Association of Certified Fraud Examiners (ACFE) and provided to the Institute for Fraud Prevention (IFP) to examine differences in the profile of financial reporting fraud (FRF) between private companies and public companies. Although private companies represent a significant portion of the economy, largely due to lack of data on these companies, most research on FRF examines only public companies. The primary objective of this study is to determine how private company FRF is different from FRF in public companies. Our multivariate tests reveal that public companies have stronger anti-fraud environments, are more likely to have frauds that involve timing differences, tend to experience larger frauds, have frauds that involve a larger number of perpetrators, and are less likely to have frauds that are discovered by accident. Overall, it appears that the stronger anti-fraud environment in public companies leads public company FRF perpetrators to use less obvious fraud methods (i.e., timing differences) and to involve larger fraud teams to circumvent the controls. These public company frauds are larger than in private companies, and their larger size may make them more likely to be detected through formal means, rather than by accident. Based on the results, we encourage auditors and others to be particularly attuned to the unique risks of the public versus private setting.

Application of Fuzzy Logic to Fraud Detection

2005 ◽  
pp. 135-139
Author(s):  
Mary Jane Lenard ◽  
Pervaiz Alam
Keyword(s):  
Financial Reporting ◽  
Average Cost ◽  
Medical Insurance ◽  
Financial Statements ◽  
Third Party ◽  
Insurance Fraud ◽  
Fraudulent Financial Reporting ◽  
The Cost ◽  
The U.S ◽  
Financial Reporting Fraud

In light of recent reporting of the failures of some of the major publicly-held companies in the U.S. (e.g., Enron & WorldCom), it has become increasingly important that management, auditors, analysts, and regulators be able to assess and identify fraudulent financial reporting. The Enron and WorldCom failures illustrate that financial reporting fraud could have disastrous consequences both for stockholders and employees. These recent failures have not only adversely affected the U.S. accounting profession but have also raised serious questions about the credibility of financial statements. KPMG (2003) reports seven broad categories of fraud experienced by U.S. businesses and governments: employee fraud (60%), consumer fraud (32%), third-party fraud (25%), computer crime (18%), misconduct (15%), medical/insurance fraud (12%), and financial reporting fraud (7%). Even though it occurred with least frequency, the average cost of financial reporting fraud was the highest, at $257 million, followed by the cost of medical/insurance fraud (average cost of $33.7 million).

Female business leaders and the incidence of fraud litigation

2017 ◽  
Vol 43 (1) ◽  
pp. 59-75 ◽  
Author(s):  
Mary Jane Lenard ◽  
Bing Yu ◽  
E. Anne York ◽  
Shengxiong Wu
Keyword(s):  
Financial Reporting ◽  
Sample Selection ◽  
Women In Leadership ◽  
Class Action ◽  
Female Executives ◽  
Data Set ◽  
Content Type ◽  
Fraud Risk ◽  
The Board Of Directors ◽  
Financial Reporting Fraud

Purpose The purpose of this paper is to examine whether companies with female executives and directors are less likely to be involved in financial reporting fraud litigation. Design/methodology/approach The authors build a data set comprised of companies from the Stanford Securities Class Action Clearinghouse database that were involved in fraud litigation along with a control set of companies listed on the Compustat database for the time period 2007-2013. The authors use a logistic regression model to determine the likelihood of fraud when there is at least one woman in an executive position or on the board of directors. Findings The authors find that the presence of at least one female leader decreases the likelihood that the company will be involved in litigation for financial reporting fraud. The results are robust after controlling for sample selection bias by using a propensity score matched sample. Practical implications The findings add to the literature which indicates that women tend to be more risk averse and are more committed to ethics policies. The study also supports previous research that indicates large firms with inflated market value are more likely to be subject to fraud litigation. Originality/value The study combines the literature on the characteristics of women in leadership positions with the study of fraud litigation. The authors find evidence that the presence of either female executives or female directors lowers financial reporting fraud risk.

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