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Today’s Discussion. Linguistic feature mining of 2 contrasting corpora:. Financial Statement Fraud: Problem and Motivation. Investors look for credibility, transparency, and clarity of financial documents to make investment decisions and to maintain confidence in companies

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today s discussion
Today’s Discussion
  • Linguistic feature mining of 2 contrasting corpora:
financial statement fraud problem and motivation
Financial Statement Fraud: Problem and Motivation
  • Investors look for credibility, transparency, and clarity of financial documents to make investment decisions and to maintain confidence in companies
  • Management’s Discussion and Analysis (MD&A) is among the sections of 10-Ks that is read most often
  • Auditors need innovative ways to assess risk based on not only financial and nonfinancial measures but also financial statement texts
deception is strategic buller and burgoon 1996
Deception Is Strategic (Buller and Burgoon, 1996)
  • FOOTNOTE 16. RELATED PARTY TRANSACTIONS
  • In 2000 and 1999, Enron entered into transactions with limited partnerships (the Related Party) whose general partner’s managing member is a senior officer of Enron. The limited partners of the Related Party are unrelated to Enron. Management believes that the terms of the transactions with the Related Party were reasonable compared to those which could have been negotiated with unrelated third parties…Subsequently, Enron sold a portion of its interest in the partnership through securitizations.” (Enron 2000)
leakage theory applied to fraudulent financial reporting ekman 1969
Leakage Theory Applied to Fraudulent Financial Reporting (Ekman 1969)
  • Managers engaging in fraud cannot completely match behavior exhibited when truthful
    • Cues leak out unintentionally
    • Language usage should leave clues to deception
mining linguistic features for detecting obfuscation in financial reports
Mining Linguistic Features for Detecting Obfuscation in Financial Reports

Do MD&A sections of fraudulent 10-Ks have a higher level of obfuscation?

Based on the research in deception detection and obfuscation, we can look for the following (among other cues) in fraudulent MD&As:

  • More complex words
  • More complex sentences
  • More causation words
  • More achievement words
slide6

Our Methodology

101 MD&As with fraud problems

101 MD&As with no fraud problems

Classified as Not Deceptive

Linguistic Extraction and Classification Tools

Classified as

Deceptive

Linguistic Cues for Deception

slide8
Application of Automated Linguistic Analysis to Transcripts of 911 Homicide Calls for Deception Detection

Caller from Columbia, Missouri

Caller from Orange County, Florida

911 calls problem motivation
911 Calls: Problem & Motivation
  • 911 calls are a potentially rich source of verbal deception indicators
    • 911 calls are unrehearsed, high-stakes communications
  • Motivation: Identify if linguistic content of truthful vs. deceptive 911 calls differs
question
Question

Can automated linguistic analysis techniques accurately classify deceptive vs. truthful callers in transcripts of 911 homicide calls?

Based on the research in deception detection, we can look for the following (among other cues) in deceptive 911 calls:

  • Higher use of they
  • Higher use of we
  • More suppressed answers, using as few words as possible --- the opposite of obfuscation!
    • Negation
    • Assent

than truthful callers.

slide11

Methodology

Twenty-five 911 Calls Labeled as Deceptive

Twenty-five 911 Calls Labeled as Truthful

Classified as Not Deceptive

Linguistic Extraction and Classification Tools

Classified as

Deceptive

Linguistic Cues for Deception

discussion truthtellers
Discussion: Truthtellers
  • Truthtellers:
    • Display more negative emotion (including emotion-filled swearing) and anxiety than deceivers.
    • Refer to singular others (she or he).
    • Use more numbers to ensure responders find address as quickly as possible or know phone number.
    • Use more generic names of locations, such as ‘apartment’ or ‘garage’ to give more accurate, helpful information to responders.
discussion deceivers
Discussion: Deceivers
  • Deceivers:
    • ‘Distance’ themselves from what is said by referencing others in the 3rd person (they).
    • Try to ‘share the blame’ by referring to self as plural (we) rather than as singular.
    • Use more negation and assent words because they are trying to subdue, constrain, or suppress answers/affect.
    • Tell the operator to ‘wait’ or ‘hold on’ if the operator is asking them to do something, such as CPR, that they are reluctant to do.