Download - Finding Fraud & Deception
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Finding Fraud & Deception
Presented by:Don Wengler, CPA/CFF, CFE, CVA
Wichita State University Accounting & Audit Conference May, 18, 2011
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Lunch, Murthy, Engle 2009
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Useful Research
“Useful research reflects results that are belief changing”
Uday Murthy lecture, March 4, 2011
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Fraud Brainstorming
SAS 99: Consideration of Fraud in a Financial Statement (AICPA 2002)
Usually face-to-face audit team discussion
Part of audit planning process
Outcome affects audit procedures performed
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Our Experiment
1. Team Nominal
2. Team Face-to-Face
3. Team Content Facilitation
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Fraud Brainstorming
FraudIdea
Generation
Relevant toClient
Not RelevantTo Client
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Face-to-Face Brainstorming- Coordinate Schedules- Wait- Attend- Remember- Avoid Cog. Inertia
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Computer-Mediated Advantages
Members can input ideas simultaneously
However, fraud brainstorming is more complex than simple idea generation
Relevant fraud risks must be identified through the interaction regarding: Specialized auditing knowledge Industry-specific factors Client-specific factors
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Florida Study
Objectives--Relative effectiveness of:
1. Electronic v. face-to-face
2. Interactive v. Nominal
3. With v. without content facilitation
Whether participating in a fraud brainstorming session heightened auditor awareness of fraud risks when present
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Florida Study
188 SAS 99 auditing students, teams of 4
Studied a company case study
5 question test assured case facts known
108 electronically/80 face-to-face
Electronic interactive; electronic nominal; face-to-face, with/without facilitation.
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Florida Study
1. Reviewed case again
2. Made initial fraud risk assessment alone
3. 20 minutes of fraud brainstorming (1221)
4. 5 prompts: Opportunity, pressure, rationalization, revenue recognition, management override of internal controls
5. Face-to-face 2nd interaction
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Florida Study: Measurement
The number of relevant fraud factors identified from the case
Change from the pre-brainstorming to post-brainstorming fraud risk assessment from 1% to 100% of estimated probability of material misstatement
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Florida Study: Results
Average Number of Relevant Fraud Risks Identified Per Team
0
2
4
6
8
10
12
14
16
Face-to-Face Electronic Nominal Electronic Interactive
No Facilitation Facilitation
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Florida Study: Conclusions
Electronic fraud brainstorming is significantly more effective than face-to-face fraud brainstorming
Interactive brainstorming is no more effective than “nominal” brainstorming
Brainstorming effectiveness is significantly higher with content facilitation, than without
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Is Abe Lincoln Honest?
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Larcker & Zakolyukina 2010
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Stanford Study
Objective: Construct and test a linguistic model for detecting deceptive CEO and CFO communications in quarterly earnings call communications.
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Stanford Study
1. Reviewed prior psychological and linguistic research related to deception
2. Identified words and uses of language that are believed to signal deception
3. Built a statistical model designed to measure/predict deception in CEO/CFO Q&A communications, based on the words/usage
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Stanford Study
4. Defined deceptive CEO and CFO communications in quarterly earnings call Q&A sessions
5. Analyzed 16,577 full text Q&A sessions to test the success of the statistical model for predicting deception CEO and CFO communications
6. Generalized conclusions
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Prior Psychological/Linguistics
Emotions perspective
Cognitive effort perspective
Control perspective
Lack of embracement perspective
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Reference Language
Larcker & Zakolyukina 2010
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Illustrative Data Table1 A B C
2
4
5 How
6 many How
7 times is deceptive
8 a word is the
9 used? communication?
10 22 100%
11 16 75%
12 12 50%
13 3 25%
14 0 0%
15
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Illustration of Positive Association22, 100%
16, 75%
12, 50%
3, 25%
0, 0%0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 5 10 15 20 25
Number of Times Word Used
Measu
re o
f D
ecep
tio
n
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Illustration of Positive Associationy = 0.043x + 0.0439
R2 = 0.981
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 5 10 15 20 25
Number of Times Word Used
Measu
re o
f D
ecep
tio
n
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Illustration of Negative Association
5, 100%
12, 75%
14, 50%
18, 25%
25, 0%0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 5 10 15 20 25 30
Number of Times Word Used
Measu
re o
f D
ecep
tio
n
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Illustration of Negative Association
y = -0.0526x + 1.2779R2 = 0.9671
-20%
0%
20%
40%
60%
80%
100%
0 5 10 15 20 25 30
Number of Times Word Used
Measu
re o
f D
ecep
tio
n
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Illustration of No Association8, 100%
16, 75%
12, 50%
3, 25%
12, 0%0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 5 10 15 20
Number of Times Word Used
Mea
sure
of
Dec
epti
on
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Illustration of No Association8, 100%
16, 75%
12, 50%
3, 25%
12, 0%
y = 0.0129x + 0.3683R2 = 0.0258
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 5 10 15 20
Number of Times Word Used
Mea
sure
of
Dec
epti
on
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Reference Language
Larcker & Zakolyukina 2010
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Positive/Negative Words
Larcker & Zakolyukina 2010
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Positive/Negative Words
Larcker & Zakolyukina 2010
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Cognitive Process
Larcker & Zakolyukina 2010
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Other Cues
Larcker & Zakolyukina 2010
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Self-constructed word categories
Reference to general knowledge
Shareholder value
Value creation
Hesitation expressions
Extreme negative emotions
Extreme positive emotions
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Stanford Study: How Was Deception Measured?Subsequent:
Form 8-K filings reflecting restatements of earnings (significant in size)
Filings reflecting “material weaknesses”
Auditor changes
Late financial statement filings
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Stanford Study: How Was Size of the Answer Uniformly Scaled?
Median CEO answer: 1,811 words
Median CFO answer: 987 words
Typical CFO: (10/1,000) X 1,000 = 10
Talkative CFO: (10/3,000) x 1,000 = 3.3
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Stan-ford Study: Model Output
Larcker & Zakolyukina 2010
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Stanford Study: Model Output
Larcker & Zakolyukina 2010
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Conclusions: Deceptive Executives
More general knowledge references
Fewer non-extreme positive emotions
Fewer references to shareholder value and value creation
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Conclusions: Deceptive CEOs
Fewer self-references
More 3rd person plural & impersonal pronouns
More extreme positive emotions
Fewer extreme negative emotions
Fewer certainty & hesitation words
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Our Survey
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Budgeting: An Experimental Investigation of the Effects
of Negotiation
Joseph F. FisherIndiana University
James R. FredericksonHong Kong University
Sean A. PefferUniversity of Kentucky
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Budget Setting
Negotiation Process
Unilateral Process
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Negotiation Matrix
Makes Initial
Budget Proposal
Has Final
Budget Authority
Superior
Subordinate
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Budget Setting Consequences
Budgetary Slack/Planning
Subordinate Performance/Motivational
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Conclusions
Budgets set through a negotiation process where superiors have final authority are lower than budgets set unilaterally by superiors.
Budgets set through a negotiation process where subordinates have final authority are not significantly different from budgets set unilaterally by subordinates.
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Conclusions
Budgets set through a negotiating process ending in agreement contain significantly less slack.
A failed negotiation followed by superiors imposing a budget has a significant detrimental effect on subordinate performance.
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Contact Information
BKD, LLPKansas City, MO 64105
816-701-0257
BKD, LLPWichita, Kansas
316-265-2811