Today’s Discussion

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Today’s Discussion • Linguistic feature mining of 2 contrasting corpora: Text from Financial Statements Transcripts of 911 Homicide Calls Text Verbal communication transcribed to text Carefully written and edited over weeks to months Unrehearsed Formal: conforms to genre for financial Informal: includes slang

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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 - PowerPoint PPT Presentation

Transcript of Today’s Discussion

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Todays DiscussionLinguistic feature mining of 2 contrasting corpora:

Text from Financial StatementsTranscripts of 911 Homicide CallsTextVerbal communication transcribed to textCarefully written and edited over weeks to monthsUnrehearsedFormal: conforms to genre for financial communiqusInformal: includes slangFinancial Statement Fraud: Problem and MotivationInvestors look for credibility, transparency, and clarity of financial documents to make investment decisions and to maintain confidence in companiesManagements Discussion and Analysis (MD&A) is among the sections of 10-Ks that is read most oftenAuditors 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)FOOTNOTE 16. RELATED PARTY TRANSACTIONS

In 2000 and 1999, Enron entered into transactions with limited partnerships (the Related Party) whose general partners 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 partiesSubsequently, Enron sold a portion of its interest in the partnership through securitizations. (Enron 2000)

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Leakage Theory Applied to Fraudulent Financial Reporting (Ekman 1969) Managers engaging in fraud cannot completely match behavior exhibited when truthfulCues leak out unintentionallyLanguage usage should leave clues to deception

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 wordsMore complex sentencesMore causation wordsMore achievement words

Our MethodologyLinguistic Extraction and Classification ToolsLinguistic Cues for DeceptionClassified as DeceptiveClassified as Not Deceptive101 MD&As with fraud problems101 MD&As with no fraud problems

6Example of ResultsGreater in Fraudulent MD&AsRate of Three Syllable Words** Conjunctions** Causation Words** Achievement Words* ** = p < .05, * = p < .107Application of Automated Linguistic Analysis to Transcripts of 911 Homicide Calls for Deception Detection

Caller from Orange County, FloridaCaller from Columbia, Missouri

8911 calls are a potentially rich source of verbal deception indicators911 calls are unrehearsed, high-stakes communications

Motivation: Identify if linguistic content of truthful vs. deceptive 911 calls differs911 Calls: Problem & Motivation

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 theyHigher use of weMore suppressed answers, using as few words as possible --- the opposite of obfuscation!NegationAssent

than truthful callers.QuestionMethodologyLinguistic Extraction and Classification ToolsLinguistic Cues for DeceptionClassified as DeceptiveClassified as Not DeceptiveTwenty-five 911 Calls Labeled as DeceptiveTwenty-five 911 Calls Labeled as Truthful

11Examples of ResultsVariable nameDirectionExample1st person pluralD>TWe don't know.3rd person pluralD>TYes, they said, they said if they heard anything they were going to my house.NegationD>TNo nothing, he's gone.AssentD>TOkay, they're here.12Truthtellers: 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: Truthtellers13Deceivers: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.

Discussion: Deceivers14Questions?