The Psychology of Consumer Fraud

Authors: Doug Shadel & Karla Pak

Publication: Doctoral Thesis

Year: 2007

Summary: This work provides a literature review of social influence (as it relates to consumer fraud) and consumer fraud victimization (including fraud’s prevalence, fraud types, and typical victim profiles).

It also introduces an undercover taping project identifying various persuasion strategies used by conmen.

  • Of 1,112 influence tactics coded across 128 transcripts, the most commonly-used tactic was “Phantom Fixation,” with 249 instances (p. 66). See page 67 for a chart of influence tactics by scam type.

The work also describes a series of fraud victim profiling studies, comparing known victims of fraud to non-victims. In so doing, it seeks to identify factors that predict victimization in two different types of fraud, while circumventing the problem of victim-denial.

  • Investment fraud victims are more likely to be financially literate, married, male, have a college degree or more, earn $35,000 per year or more, and are more open to persuasive appeals (p.157).
  • Lottery fraud victims are more likely to be female, widowed, living alone, earn less than $30,000 per year, be less financially literate, and “live for today” (p. 158)

The survey also found that many known victims were unwilling to acknowledge their victimization:

  • When asked simply, only 10-20% of investment victims and 14-56% of lottery victims would acknowledge having been defrauded, with the rate depending on the question phrasing (p. 150).
  • The secondary study of just investment victims was able to attain 62% acknowledgement using a series of progressive, investment-specific questions (p. 150).

The survey included 80 known lottery fraud victims, 80 investment fraud victims (9 self-identified), and 160 general population (self-identified as non-victims).

Author Abstract: This study was a three-part inquiry of consumer fraud. In part 1, undercover tapes of fraud pitches were analyzed to determine how con men pitch their victims. Tape analysis revealed con criminals customize their pitch to match the psychological profile of the victim and use a complex combination of influence tactics within each pitch to persuade. In part 2, a 72 question survey was administered to 80 victims of lottery fraud, 80 victims of investment fraud and 160 non-victims of fraud. Investment fraud victims demonstrated a better understanding of basic financial literacy than non-victims. Both investment and lottery victims were more likely to have experienced a negative life event unrelated to their fraud experience. Both victim types were more likely to listen to sales pitches from unknown sales persons. Investment and lottery fraud victims both dramatically underreport fraud. In part 3, a 2nd survey was administered to a different population of 125 investment fraud victims and 258 non-victims to determine if findings from survey 1 could be replicated. In fact, major findings relating to financial literacy were replicated, as were demographic, psychological and behavioral characteristics of investment fraud victims. In addition, new findings relating to “persuasion literacy” were found: victims of investment fraud were less able to identify pitch lines used by con men in fraud schemes than a non-victim population. This suggests that a key strategy for deterring fraud victimization in the future might be to teach both financial literacy and persuasion literacy to investors.

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Modeling the Underreporting Bias in Panel Survey Data

Authors: Sha Yang (Leonard N. Stern School of Business, New York & School of Economics and Management, China), Yi Zhao (J. Mack Robinson College of Business, Georgia), Ravi Dhar (Yale School of Management, Connecticut)

Publication: Marketing Science

Year: 2010

Focus Area: Impact, Research method development

Relevance: Surveys are used extensively to determine the prevalence and impact of financial fraud.  Given the sensitivity of the topic, it is also particularly prone to underreporting biases in surveys, as respondents are reluctant to admit their own victimization.  Determining this rate of underreporting is essential to untangling fraud’s actual social and economic impact.

Summary: While underreporting has been documented (Turner 1961, Waksberg and Neter 1965, Lee, Hu and Toh 2000) and modeled (Bailar 1975, Bollinger and David 1997) in other studies, this paper proposes a more sophisticated means of quantifying its impact.

  • By studying both reported behavior and partially observed behavior, the authors propose a mathematical modeling framework that determines who is underreporting, when, and how much.
  • This model allows collected information to be accurately interpreted, provides computation of true behavioral incidence, and identifies particular demographic and psychological characteristics that correlate with increased underreporting (such as sex, age, income, and motivation).
  • For example, in a study examining drinking habits (water and soft drinks), rates of underreporting varied with specific psychological and demographic characteristics (women reported less than men; those inclined to indulge reported less than those motivated by “looking good” and “health”).
  • By identifying factors that correspond with underreporting, the model highlights options to intervene in a targeted manner, and encourage full and accurate participation by respondents (such as incentives).

While this model is intended for longitudinal survey panel reporting, it has promise for similarly rigorous computational analysis of one-time surveys (commonly used to identify the rate of fraud).

Author Abstract: Panel survey data have been gaining importance in marketing. However, one challenge of estimating econometric models based on panel survey data is how to account for underreporting; that is, respondents do not report behavioral incidences that actually occur. Underreporting is especially likely to occur in a panel survey because the data-recording mechanism is often tedious, complex, and effortful. The probability of underreporting is likely to vary across respondents and also over the duration of the survey period. In this paper, we propose a model to simultaneously study reported behavioral incidences and partially observed actual behavioral incidences. We propose a Bayesian approach for estimating the proposed model. We treat those unobserved actual behavioral incidences as latent variables, and the Gibbs sampler makes it convenient to impute the nonreported consumption incidences along with making inferences on other model parameters. Our proposed method has two advantages. First, it offers a model-based approach to remove the underreporting bias in panel survey data and therefore allows marketing researchers to make accurate inferences about consumers’ actual behavior. Second, the method also offers a natural way to study factors that influence respondents’ propensity to underreport. Because we treat those underreported behavioral incidences as nonmissing at random, this underreporting propensity varies across respondents and over time. This understanding can help marketing researchers design the right strategy to intervene and incentivize respondents to authentically report and hence improve the quality of survey data. The proposed model and estimation approach are tested on both synthetic data and actual panel survey data on consumer-reported beverage-drinking behavior. Our analysis suggests that underreporting can significantly mask respondents’ true behavior.

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