Occupational Fraud: Does Gender Matter?

10. 12. 2022
Štítky

This journal article examines whether gender impacts occupational fraud in Canadian small and medium businesses. It used the T.test statistic tool. The work could have used other techniques, but the t.test was adequate for the two data evaluations. Some precedent studies on the gender implications of fraud have used the Mean, Median, and other methods, resulting in different outcomes. However, applying the t.test has resulted in no significant difference in gender occupational fraud. The article recommends a transformation of the mindset of a fraudster. Future researchers can collect more data and use other statistical techniques more accurately.

Introduction

Precedent research papers published different positions on gender implications in occupational fraud based on the geographical data collected. The first group, including A.C.F.E. ( 2002 – 2022) report to the nations in general and mainly the Canadian edition, affirmed that males were more likely to commit occupational fraud.

The second group discussed that females are perhaps more likely to be involved in occupational fraud. For instance, Benson &Chio (2019) Argued that women are also somewhat more involved in occupational crime now than in the past, but the sex distribution of offenders has not been nearly as dramatic as the change in race and ethnicity.

The third group, including Ramamoorti et al., found that committing occupational fraud is not only about gender but the behavior, stating that behavior is the root cause of fraud, and someone can identify it by observing an individual (Bad Apple), a group (Bad Bushel), or a community’s actions (Bad Crop). The worst is the bad crop. At this level, fraud eventually becomes a culture in the congregation, from the leaders to the assistants and workers. (Ramamoorti et al., 2009)

The fourth group points to the risks and needs that could be categorized as perceived pressure. Benson &Harbinson (2020) found that gender predicted proactive, reactive, and general criminal thinking after controlling for other factors: on average, women scored higher than men on all three scales. However, the results also showed that measures of risk and needs were stronger predictors of criminal thinking than gender.

It is essential to underline that based on the data formally collected, the result displayed in the Ph.D. dissertation of umba (2021) lined up with the first research group supporting a significant difference in gender impact on occupational fraud.

However, this paper gathered additional data from A.C.F.E. (2002 – 2022), aiming to examine whether there is a significant difference in gender involvement in occupational fraud.

Question: Is there a significant difference in gender involvement in occupational fraud?

Even though the data was gathered from various small and medium business organizations in Canada between 2002-2022, the mean displayed male avant-garde. Whether there is a significant difference in gender involvement in occupational fraud is questioned. This paper aims to examine the gender implications of occupational fraud.

Methods

The paper examined the impact of gender on occupational fraud. Besides the mean and median test results from the A.F.C.E. (2002 - 2022) report to the nation’s Canadian edition. The paper used the excel data analysis tool t.test to examine the data. This approach seems acceptable to analyze two groups of data to test whether the means of two populations are equal.

Results

The paper examines whether there is a significant difference in gender involvement in occupational fraud in Canadian small and medium businesses. The work recognizes the difficulties of collecting data from primary sources directly from affected Canadian small and medium business organizations—however, the paper data is from a secondary source. The data collected was found relevant to the questions paused in this paper; however, more data should be needed for further study.

This section addressed data presentation, T. Test analysis, and findings. 

Data presentation

The data on gender perpetrators was collected from A.F.C.E. (2002 – 2022) report to the nation’s Canadian edition, arranged in a table and displayed in a figure.

Table 1: Frequency of gender perpetrators in %

Year

Male %

Female %

2002

53.50

46.50

2004

52.90

47.10

2006

61.00

39.00

2008

59.10

40.90

2010

58.10

41.90

2012

48.10

51.90

2014

54.70

45.30

2016

64.60

35.40

2018

48.20

52.00

2020

59.00

41.00

2022

62.00

38.00

 

 

Figure 1

Umba, C. (2022)

T. test Analysis

 

t-Test: Two-Sample Assuming Equal Variances

 
     

 

Variable 1

Variable 2

Mean

56.47272727

43.5454545

Variance

29.63218182

29.9667273

Observations

11

11

Pooled Variance

29.79945455

 

Hypothesized Mean Difference

0

 

df

20

 

t Stat

5.553721513

 

P(T<=t) one-tail

9.75847E-06

 

t Critical one-tail

1.724718243

 

P(T<=t) two-tail

1.95169E-05

 

t Critical two-tail

2.085963447

 

Umba, C. (2022)

 

Results interpretation:

Mean: The Mean of each sample.

  • Sample 1 Mean: 56.47
  • Sample 2 Mean: 43.55

Variance: The number of observations in each sample.

  • Sample1 Observations: 11
  • Sample 2 Observations: 11

Pooled Variance: The average variance of the samples, calculated by “pooling” the variances of each sample together using the following formula:

  • s2p = ((n1-1) s21 + (n2-1) s22) / (n1+n2-2)
  • s2p = ((11-1)56.47 + (11-1)43.55) / (11+11-2)
  • s2p = 29.79945455

Hypothesized means difference; The number that “hypothesize” is the difference between the two population means. In this case, the paper chose 0 to test whether the difference between male and female population means is 0.

df: The degrees of freedom for the t-test, calculated as:

  • df = n1 + n2 – 2
  • df = 11 + 11 – 2
  • df = 20

t Stat: The test statistic t, calculated as:

  • t = (x1 – x2) / √s2p(1/n1 + 1/n2)
  • t = (56.47-43.55) / √29.79945455(1/11+1/11) 
  • t = 5.553721513

P(T<=t) two-tail: The p-value for a two-tailed t-test. It can also be found using T Score to P Value Calculator t = 5.553721513 with 20 degrees of freedom.

In this case, p = 1.95169E-05. It is larger than 0.05, so there is insufficient evidence to indicate a gender difference in occupational fraud, even though the mean displays the difference.

T Critical two-tail: The critical value with 20 degrees of freedom in this case.

And 95% confidence level turns out to be 2.085963447, and the statistic t is less than this value. It seems that there is not enough evidence to support gender differences when it comes to occupational fraud. 

Findings

The T. test result shows no significant difference in gender involvement in occupational fraud within small and medium Canadian businesses, even though the mean displays it.

Discussion

The paper sought to understand whether gender involvement in an occupational fraud matter. Precedent studies have examined the gender implications of occupational fraud from different angles and found that males were more involved in occupational fraud than females.

 A.C.F.E’s (2002-2022) report to the nation shows the mean and median results that show males to be more implicated in occupational fraud than females, which seem caused by the plethora of males in the workplace and mostly in leadership positions. However, the T. test result from this paper shows no significant difference in gender involvement in occupational fraud within small and medium Canadian businesses.

 The following parts discuss some precedent studies on gender implications and this paper’s finding of no significant difference in gender involvement in the fraud.

Precedent studies

Searching for answers to occupational fraud is not new; some studies discussed different approaches. First, it suggests that increasing the number of female leaders could decrease occupational fraud.

However, Izevbekhai and Ohiokha (2017) argue that female presence did not reduce financial fraud. The data analyzed seems limited to a geographical environment where females are less represented; therefore, collecting more varied data may change the assertion. 

Hilliard &Neidermeyer (2018) argue that female fraudsters are more likely than male fraudsters to commit asset misappropriation in the following geographical regions: Africa (three times as likely), Asia (twice as likely), Canada (three times as likely), China (five times as likely), Europe (twice as likely), the Middle East (four times as likely), Oceania (four times as likely), the United Kingdom (eight times as likely) and the United States of America (twice as likely). In the context of this work, Canada’s female fraudster is likely to commit fraud three times as possible.

However, Hilliard & Niedermeyer’s work did not examine the other two parts of the fraud tree, which are corruption and financial statements fraud; it could have revealed different results.

Dodge (2019) From 1939 until the 1970s, the study reveals that fraud was male-centric because they were more exposed to multiple opportunities to engage in fraud than women. Contrary to that, Maulidi et al. (2022) argue that females were less engaged in the occupation, and this association is contingent on governance mechanisms. For example, they were not investing in gender-diverse leadership.

Lazarus et al. (2022), their research discloses no differences between men and women concerning socio-economic cybercrime. It emphasizes the gendered side as more in psychosocial cybercrimes but is limited to socio-economic cybercrimes. Fraud does not have gender, but the behavior of a fraudster impacts occupational fraud.

Setyaki et al. (2022) indicate that Machiavellian students (male and female) with A-type personalities are more likely to commit academic fraud under more significant academic environmental pressures. The fact is that everyone can feel pressure, which is also considered one of the three elements of the fraud triangle. However, someone should first identify the opportunity and rationalization before commuting fraud because the opportunity is the element that seems to activate a dormant intention.

World Health Organization (2017) shows that “Gender” implies the collectively constructed roles, behaviors, activities, and attributes a given society considers appropriate for men and women. 

Dearden & Gottschalk (2020) argue that male and female offenders vary in their perceptions of convenience when considering alternative crime categories and alternative categories of victims. Here perceptions of convenience are the same as the opportunity to commit fraud, which is not manifested when there is no opportunity. However, the behavior of a fraudster could reveal the hidden intention.

Ramamoorti (2008) utilized sociological and psychological approaches to research fraud. As a result, he found that the root cause of fraud is behavior. A year later, Ramamoorti et al. (2009) resolved this after a Deep study on fraud and proposed the A-B-C model to analyze and categorize fraud. Ramamoorti’s approach presents that A bad Apple refers to individual fraud, which an individual commits, and a Bad Bushel refers to a collusive fraud, where collaboration amongst management personnel allows the perpetration of fraud. Furthermore, a Bad Crop refers to fraud committed in collusion with cultural and social mechanisms that affect fraud.

According to Ramamoorti et al. (2009), the most dangerous is a Bad crop among the A.B.C. stage of the fraud analysis model. A Bad Crop characterizes leaders’ moral deficiency in an organization, which quickly spreads to their subordinates. Since it spreads throughout the organization, fraud eventually becomes a culture performed in the congregation, from the leaders to the assistants. Dorminey et al. (2012) called a bad crop an epidemic. Because it will affect a large population and pollute most of society, ethics usually must come from top to bottom. Nevertheless, employees should buy into themselves to change their ways.

No significant difference in gender 

On the promise of a search for gender impact on occupational fraud, the paper finds no significant difference in gender involvement in occupational fraud within small and medium Canadian businesses. Contrary to what precedent findings, for instance, the median by A.C.F.E. (2002-2022) and the mean displayed in the result section. This result is different because the data on which precedent studies based their analysis and the statistical methods showed males were more involved in occupational fraud than females.

As one can see, Observing the data in table 1 and figure 1 displayed a difference in percentage with males more involved in fraud, but the result generated from t. test technique is quite far different. The difference comes from the data gathered and the various statistical methods, such as the t.test. The result shows no significant difference in gender regarding occupational fraud, and perhaps using different tools may change the outcome.

Therefore, more data from different geographical places and other statistical measuring tools seem essential to further the study. Based on the no significant difference between males and females in occupational fraud, the work suggests a transformation of a person’s mind.

Recommendation

Transformation (change) Of A Fraudster’s Mindset

Dweck & Yeager (2019)present two kinds of mindset, fixed and growth. A growth mindset is a belief that human capacities and qualities are not fixed but can change and develop over time.

In this case, the problem is not gender, different methods, tools, and models that previous scholars and leaders have produced and utilized but the human mind. The mind is one of the critical factors and is at the center of increased fraudulent behaviors in occupational fraud.

When the mind’s problem is addressed and fixed, everything inside and outside a person shall align with the perceived business ethics and produce the expected result. 

The mind of a person in the brain is like software in hardware. The longer a person lives in the world, grows in stature, and collects more data may require new software to deal with a unique experience. 

Socrates and Plato sustain that the mind and body have different substances. Following many other early philosophers, Descartes argued that the mind or reason is composed of a foreign substance to the brain, a sense that thinks independently from the body. The mind-body called it dualism. Plato reasoned that the mind and body are fundamentally different because the mind is rational, which means examining the mind can lead to truth. In contrast, he said that one could not believe anything they experience via the senses, which are part of the body, because it could be tricky. He noted that unexamined life is not worth living. Thus, Plato did not trust the senses because one can confuse reality with imagination.

Additionally, many consider that the mind is still one of the biggest mysteries in science. McGinn (1989) said they have been trying to solve the mind-body problem for a long time, and it has stubbornly resisted our best effort. And he said that It is time to admit they cannot resolve the mystery.

It is impossible to read the mind of another person. Regardless of the new technology’s performance, the tools developed lack precision in reading the human mind—for example, the failure of polygraph machines. Humans have learned how to manipulate the device and change the outcome.

Moreover, stats show that psychologists have developed various approaches, such as Maslow’s hierarchy of needs to palliate and bring solutions to the work environment. The aim was to understand the five tiers of needs and fix for equilibrium but still unsatisfied to see the C.E.O.’s exorbitant benefices. However, Maslow’s theory touches only on the body or social satisfaction but fails to respond to the mind’s problem. 

Moreover, companies have utilized other techniques to discourage fraudulent financial behaviors by using advantages and promotions—for example, the carrot and stick approach. 

However, the stats show that these methods are still far from satisfying the mind. In contrast, if this method could work better as expected, no C.E.O., C.F.O., and other C-levels could not involve themselves in asset misappropriation and corruption. So, an appetite indeed comes from eating! 

Descartes proposed the notion of causal interaction to solve the problem of the mind. Because the two, body and mind, can influence each other differently. The mind and body are working together, despite obeying different physical laws. However, Descartes did not explain how this could proceed. Observe that the reason must have some control over the body; this is evident when one decides to move. In turn, the body has some control over our minds; this is evident when we feel pain. Understanding the mind’s functionality is excellent, but training the mind as one prepares the body daily is more.

Transforming a mindset requires the development of a new ideology (philosophy) at the workplace. For instance. Psychological interventions that change mindsets (Yeager & Dweck, 2012).

Thus, the expected change in behavior should contribute to a decrease in occupational fraud. 

Conclusion

This journal paper aimed to examine whether there was a significant difference in gender involvement in occupational fraud. The work used the t.test statistical method to analyze the data gathered from A.C.F.E. (2002 – 2022) report to the nations the Canadian edition. The result indicates that there is not a significant difference in gender concern in fraud. Precedent studies have used the mean and median statistical tools and have suggested that males were more likely to commit occupational fraud than women. The work indicated the transformation (change) Of a fraudster’s mindset. Future studies can collect more data and use other statistical tests to advance the search.

 

References

Association of Certified Fraud Examiners. (n.d.). Report to The Nations Canadian Edition. In Acfe.Com.

Benson, M. L., &Chio, H. L. (2019). Who Commits Occupational Crimes? The Handbook of WhiteCollar Crime, 95–112. https://doi.org/10.1002/9781118775004.ch7

Benson, M. L., &Harbinson, E. (2020). Gender and criminal thinking among individuals convicted of white-collar crimes. Criminal Justice Studies, 33(1), 46–60.

Dearden, T., & Gottschalk, P. (2020). Gender and White-Collar Crime: Convenience in Target Selection. Deviant Behavior42(11), 1485–1493. https://doi.org/10.1080/01639625.2020.1756428

Dodge, M. (2019). Women and White-Collar Crime. Oxford Research Encyclopedia of Criminology and Criminal Justice. https://doi.org/10.1093/acrefore/9780190264079.013.493

Dorminey, J., Fleming, A. S., Kranacher, M. J., & Riley, R. A. (2012). The Evolution of Fraud Theory. Issues in Accounting Education27(2), 555–579. https://doi.org/10.2308/iace-50131

Dweck, C. S., & Yeager, D. S. (2019). Mindsets: A View From Two Eras. Perspectives on Psychological Science14(3), 481–496. https://doi.org/10.1177/1745691618804166

Hilliard, T., &Neidermeyer, P. E. (2018). The gendering of fraud: an international investigation. Journal of Financial Crime25(3), 811–837. https://doi.org/10.1108/jfc-08-2017-0074

Izevbekhai, M. O., &Ohiokha, G. (2017). Board Composition and Financial Statement Fraud. Nigerian Academy of Management Journal, 12(2), 119–134.

Lazarus, S., Button, M., &Kapend, R. (2022). Exploring the value of feminist theory in understanding digital crimes: Gender and cybercrime types. The Howard Journal of Crime and Justice61(3), 381–398. https://doi.org/10.1111/hojo.12485

Maulidi, A., Shonhadji, N., Fachruzzaman, F., Sari, R. P., Nuswantara, D. A., &Widuri, R. (2022). Are female CFOs more ethical to the occurrences of financial reporting fraud? Theoretical and empirical evidence from cross-listed firms in the US. Journal of Financial Crime. https://doi.org/10.1108/jfc-07-2022-0170

MCGINN, C. (1989). Can We Solve the Mind–Body Problem? MindXCVIII(391), 349–366. https://doi.org/10.1093/mind/xcviii.391.349

Ramamoorti, S. (2008). The Psychology and Sociology of Fraud: Integrating the Behavioral Sciences Component Into Fraud and Forensic Accounting Curricula. Issues in Accounting Education23(4), 521–533. https://doi.org/10.2308/iace.2008.23.4.521

Ramamoorti, S., Morrison, D., &Koletar, J. W. (2009). Bringing Freud to Fraud: Understanding the State-of-Mind of the C-Level Suite/White Collar Offender through “A-B-C” Analysis. ECommons, 71. https://ecommons.udayton.edu/acc_fac_pub/71/

Setyaki, R. S., Pesudo, D. A. A., Andreas, H. H., & Chang, M. L. (2022). Does Personality Impact Academic Fraud? Review of Integrative Business and Economics Research, 11(3), 81–98.

Umba, C. (2021). Fraudulent Accounting/Financial Behaviors: Impact on Small & Medium Canadian Business Organizations. [PhD Dissertation]. LIGS University.

World Health Organization. (2017). Gender, Women, and Health. Web.Archive.Org. https://web.archive.org/web/20170130022356/http://apps.who.int/gender/whatisgender/en/

 

Author: Christopher Umba, student LIGS University
Approved by: Dr. Minh Nguyen, lecturer LIGS University

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