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Fraud Examination [Mas Sugeng]. Chapter 1: Introduction.

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Presentation on theme: "Fraud Examination [Mas Sugeng]. Chapter 1: Introduction."— Presentation transcript:

1 Fraud Examination [Mas Sugeng]

2 Chapter 1: Introduction

3 What is Occupational/hub Fraud and Abuse? Use of occupation / hub For personal enrichment/memperkaya Through deliberate misuse or misapplication / sengaja meneruskan Of employer’s resources/assets

4 Defining Fraud / penipuan Four elements: Material false statement Knowledge that the statement was false Reliance (percaya) on the statement by victim Damages/perusakan

5 Defining Abuse / salah guna A deceitful act / tindakan bohong A corrupt practice or custom / praktek, kebiasaan korup Examples: –“Borrow” company equipment –Use sick leave when not sick –Slow or sloppy work / pelan dan lemah kerja –Surf the Net at work / jaringan lbh batas –Work under influence of drugs/alcohol

6 Research in Occupational Fraud and Abuse

7 Edwin H. Sutherland First defined “white-collar crime” –Criminal acts of corporations –Individuals in corporate capacity Theory of differential association –Crime is learned –Not genetic –Learned from intimate personal groups

8 Donald R. Cressey Studied embezzlers Why people become “trust violators” Developed the Fraud Triangle

9 The Fraud Triangle PRESSURE PERCEIVED OPPORTUNITY RATIONALIZATION

10 Nonsharable Problems Violation/pelangaran of ascribed obligations Personal failures Business reversals /rugi Physical isolation Status gaining Employer-employee relations

11 Cressey’s Offender/pelanggar Types Independent businessmen –“Borrowing” –Funds really theirs Long-term violators –“Borrowing” –Protect family –Company cheating them –Company generally dishonest

12 Cressey’s Offender Types Absconders / menghindar Take the money and run Usually unmarried, loners Blame “outside influences” or “personal defects”

13 W. Steve Albrecht Nine motivators of fraud 1.Living beyond means 2.Overwhelming desire for personal gain 3.High personal debt 4.Close association with customers 5.Pay not commensurate with job

14 W. Steve Albrecht Nine motivators of fraud 6.Wheeler-dealer 7.Strong challenge to beat system 8.Excessive gambling 9.Family/peer pressure

15 The Fraud Scale Situational pressures –Immediate problems with environment –Usually debts/losses Perceived opportunities –Poor controls Personal integrity –Individual code of behavior

16 The Fraud Scale

17 Richard C. Hollinger Hollinger-Clark study (1983) Surveyed 10,000 workers Theft caused by job dissatisfaction True costs vastly understated

18 Employee Deviance Two categories: –Acts against property –Production violations (goldbricking) Strong relationship: theft and concern over financial situation

19 Age and Theft Direct correlation Younger employees less committed But, higher position = bigger theft Opportunity is only a secondary factor

20 Job Satisfaction and Deviance Dissatisfied employees –More likely to break rules –Regardless of age/position –Trying to right perceived inequities Wages in kind

21 Organizational Controls Some impact, but limited Hollinger studied five aspects: –Company policy –Selection of personnel –Inventory control –Security –Punishment

22 Hollinger’s Conclusions Employee perception of controls is important Increased security may hurt, not help Employee-thieves exhibit other deviance –Sloppy work, sick leave abuses, etc. “Hydraulic effect” Management should be sensitive to employees Pay special attention to young employees

23 Hollinger’s Conclusions Four key aspects of policy development 1.Understand theft behavior 2.Spread positive info on company policies 3.Enforce sanctions 4.Publicize sanctions

24 The Report to the Nation on Occupational Fraud and Abuse Largest fraud study ever Study of 2,608 fraud cases Reported by CFEs Total: $15 billion in losses $22 to $2.5 billion

25 Costs How to measure? Orgs don’t know what they lose Opinions of CFEs Six percent of gross revenues $400 billion per year Twice the U.S. defense budget

26 Position in the Organization - Cases

27 Position in the Organization – Median Loss

28 Median Loss by Gender

29 Median Loss by Age Direct and linear correlation between age and median loss Older tend to occupy higher ranking positions Greater access to revenues, assets, resources 5

30 Median Loss by Age

31 Median Loss by Marital Status

32 Median Loss by Education

33 Median Loss Per Number of Employees

34 Classifying Occupational Fraud and Abuse

35 Number of Cases by Scheme Type

36 *Represents size of misstatement rather than actual cash loss Median Loss by Scheme Type


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