The Experts below are selected from a list of 3939 Experts worldwide ranked by ideXlab platform
Linda L. Golden - One of the best experts on this subject based on the ideXlab platform.
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Pridit Is a Useful Technique for Detecting Consumer Fraud When No Training Sample Is Available
Marketing Challenges in a Turbulent Business Environment, 2016Co-Authors: Linda L. Golden, Patrick L. Brockett, John Betak, Mark I. Alpert, Montserrat Guillén, Richard A. DerrigAbstract:Marketing researchers and managers often face situations with incomplete information for decision-making. For example, when information needed for classification into strategic customer groups is lacking because of a disclosure social desirability bias. Consumers misbehaving through Fraud are unlikely to self-disclose those actions. This is an increasing global problem for services and retailers. Detection of Consumers misbehaving can be methodologically more difficult than studying other customer behaviors, since there may be no known observable dependent variable from surveys or observation for training standard statistical models.
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assessing Consumer Fraud risk in insurance claims an unsupervised learning technique using discrete and continuous predictor variables
The North American Actuarial Journal, 2009Co-Authors: Patrick L. Brockett, Linda L. GoldenAbstract:We present an unsupervised learning method for classifying Consumer insurance claims according to their suspiciousness of Fraud versus nonFraud. The predictor variables contained within a claim file that are used in this analysis can be binary, ordinal categorical, or continuous variates. They are constructed such that the ordinal position of the response to the predictor variable bears a monotonic relationship with the Fraud suspicion of the claim. Thus, although no individual variable is of itself assumed to be determinative of Fraud, each of the individual variables gives a "hint" or indication as to the suspiciousness of Fraud for the overall claim file. The presented method statistically concatenates the totality of these "hints" to make an overall assessment of the ranking of Fraud risk for the claim files without using any a priori Fraud-classified or labeled subset of data. We first present a scoring method for the predictor variables that puts all the variables (whether binary "red flag indicators," ordinal categorical variables with different categories of possible response values, or continuous variables) onto a common 1 to 1 scale for comparison and further use. This allows us to aggregate variables with disparate numbers of potential values. We next show how to concatenate the individual variables and obtain a measure of variable worth for Fraud detection, and then how to obtain an overall holistic claim file suspicion value capable of being used to rank the claim files for determining which claims to pay and the order in which to investigate claims further for Fraud. The proposed method provides three useful outputs not usually available with other unsupervised methods: (1) an ordinal measure of overall claim file Fraud suspicion level, (2) a measure of the importance of each individual predictor variable in determining the overall suspicion levels of claims, and (3) a classification function capable of being applied to existing claims as well as new incoming claims. The overall claim file score is also available to be correlated with exogenous variables such as claimant demographics or high volume physician or lawyer involvement. We illustrate that the incorporation of continuous variables in their continuous form helps classification and that the method has internal and external validity via empirical analysis of real data sets. A detailed application to automobile bodily injury Fraud detection is presented.
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assessing Consumer Fraud risk in insurance claims an unsupervised learning technique using discrete and continuous predictor variables
The North American Actuarial Journal, 2009Co-Authors: Patrick L. Brockett, Linda L. GoldenAbstract:Abstract We present an unsupervised learning method for classifying Consumer insurance claims according to their suspiciousness of Fraud versus nonFraud. The predictor variables contained within a claim file that are used in this analysis can be binary, ordinal categorical, or continuous variates. They are constructed such that the ordinal position of the response to the predictor variable bears a monotonic relationship with the Fraud suspicion of the claim. Thus, although no individual variable is of itself assumed to be determinative of Fraud, each of the individual variables gives a “hint” or indication as to the suspiciousness of Fraud for the overall claim file. The presented method statistically concatenates the totality of these “hints” to make an overall assessment of the ranking of Fraud risk for the claim files without using any a priori Fraud-classified or -labeled subset of data. We first present a scoring method for the predictor variables that puts all the variables (whether binary “red flag...
Patrick L. Brockett - One of the best experts on this subject based on the ideXlab platform.
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Pridit Is a Useful Technique for Detecting Consumer Fraud When No Training Sample Is Available
Marketing Challenges in a Turbulent Business Environment, 2016Co-Authors: Linda L. Golden, Patrick L. Brockett, John Betak, Mark I. Alpert, Montserrat Guillén, Richard A. DerrigAbstract:Marketing researchers and managers often face situations with incomplete information for decision-making. For example, when information needed for classification into strategic customer groups is lacking because of a disclosure social desirability bias. Consumers misbehaving through Fraud are unlikely to self-disclose those actions. This is an increasing global problem for services and retailers. Detection of Consumers misbehaving can be methodologically more difficult than studying other customer behaviors, since there may be no known observable dependent variable from surveys or observation for training standard statistical models.
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assessing Consumer Fraud risk in insurance claims an unsupervised learning technique using discrete and continuous predictor variables
The North American Actuarial Journal, 2009Co-Authors: Patrick L. Brockett, Linda L. GoldenAbstract:We present an unsupervised learning method for classifying Consumer insurance claims according to their suspiciousness of Fraud versus nonFraud. The predictor variables contained within a claim file that are used in this analysis can be binary, ordinal categorical, or continuous variates. They are constructed such that the ordinal position of the response to the predictor variable bears a monotonic relationship with the Fraud suspicion of the claim. Thus, although no individual variable is of itself assumed to be determinative of Fraud, each of the individual variables gives a "hint" or indication as to the suspiciousness of Fraud for the overall claim file. The presented method statistically concatenates the totality of these "hints" to make an overall assessment of the ranking of Fraud risk for the claim files without using any a priori Fraud-classified or labeled subset of data. We first present a scoring method for the predictor variables that puts all the variables (whether binary "red flag indicators," ordinal categorical variables with different categories of possible response values, or continuous variables) onto a common 1 to 1 scale for comparison and further use. This allows us to aggregate variables with disparate numbers of potential values. We next show how to concatenate the individual variables and obtain a measure of variable worth for Fraud detection, and then how to obtain an overall holistic claim file suspicion value capable of being used to rank the claim files for determining which claims to pay and the order in which to investigate claims further for Fraud. The proposed method provides three useful outputs not usually available with other unsupervised methods: (1) an ordinal measure of overall claim file Fraud suspicion level, (2) a measure of the importance of each individual predictor variable in determining the overall suspicion levels of claims, and (3) a classification function capable of being applied to existing claims as well as new incoming claims. The overall claim file score is also available to be correlated with exogenous variables such as claimant demographics or high volume physician or lawyer involvement. We illustrate that the incorporation of continuous variables in their continuous form helps classification and that the method has internal and external validity via empirical analysis of real data sets. A detailed application to automobile bodily injury Fraud detection is presented.
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assessing Consumer Fraud risk in insurance claims an unsupervised learning technique using discrete and continuous predictor variables
The North American Actuarial Journal, 2009Co-Authors: Patrick L. Brockett, Linda L. GoldenAbstract:Abstract We present an unsupervised learning method for classifying Consumer insurance claims according to their suspiciousness of Fraud versus nonFraud. The predictor variables contained within a claim file that are used in this analysis can be binary, ordinal categorical, or continuous variates. They are constructed such that the ordinal position of the response to the predictor variable bears a monotonic relationship with the Fraud suspicion of the claim. Thus, although no individual variable is of itself assumed to be determinative of Fraud, each of the individual variables gives a “hint” or indication as to the suspiciousness of Fraud for the overall claim file. The presented method statistically concatenates the totality of these “hints” to make an overall assessment of the ranking of Fraud risk for the claim files without using any a priori Fraud-classified or -labeled subset of data. We first present a scoring method for the predictor variables that puts all the variables (whether binary “red flag...
John A. Rothchild - One of the best experts on this subject based on the ideXlab platform.
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Making the Market Work: Enhancing Consumer Sovereignty Through the Telemarketing Sales Rule and the Distance Selling Directive
Journal of Consumer Policy, 1998Co-Authors: John A. RothchildAbstract:This article analyzes the provisions of the Telemarketing Sales Rule, which the Federal Trade Commission promulgated in 1995 pursuant to the 1994 Telemarketing and Consumer Fraud and Abuse Prevention Act. The author proposes a framework through which the Rule may be understood as embodying a regulatory strategy of controlling abusive telemarketing by enhancing the effectiveness of market forces. In particular, the Rule works by improving the quantity and quality of information flowing to Consumers, preventing the occurrence of transactions that the Consumer does not truly intend, preventing telemarketers from evading the effects of market forces governing availability of payment mechanisms, and enhancing the effectiveness of the contract regime. The article then applies the same framework to the 1997 Distance Selling Directive of the European Union, yielding several recommendations that EU member countries may find useful when transposing the Directive into national law. The author also discusses some of the special considerations that EU member countries should take account of when transposing the Directive's requirements in the context of electronic commerce.
Kristy Holtfreter - One of the best experts on this subject based on the ideXlab platform.
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Efforts to Reduce Consumer Fraud Victimization Among the Elderly The Effect of Information Access on Program Awareness and Contact
Crime & Delinquency, 2016Co-Authors: Daniel P. Mears, Michael D. Reisig, Samuel J. A. Scaggs, Kristy HoltfreterAbstract:Concern about the risk of Consumer Fraud victimization among the elderly has led to programs that disseminate Fraud prevention information and provide services. However, little is known about how seniors access such information or learn about or contact these programs. Drawing on scholarship on Fraud, media consumption, and the fear of crime, this study contributes to efforts to understand and reduce Consumer Fraud victimization. Analyses of data from adults age 60 and above demonstrate that certain segments of the elderly population access a greater variety of information sources to learn about Fraud prevention. In turn, such access is associated with greater Fraud prevention program awareness and contact.
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Fraud victimization and confidence in Florida's legal authorities
Journal of Financial Crime, 2007Co-Authors: Michael D. Reisig, Kristy HoltfreterAbstract:Purpose – This study seeks to identify personal characteristics that help to explain variation in Consumer confidence in legal authorities' ability to effectively deal with Fraud victimization in the State of Florida.Design/methodology/approach – The study uses cross‐sectional survey data from 918 adults who participated in a telephone interview in 2004 and 2005. Univariate statistics are used to describe the distribution of the dependent variable (i.e. Consumer confidence in legal authorities). Hypotheses are tested using bivariate and multivariate statistical techniques.Findings – Results show that less than one‐half of respondents (48.2 percent) report that they have either “a great deal” or “quite a bit” of confidence in the ability of legal authorities to respond to Consumer Fraud victimization. Bivariate correlations show that younger respondents, those with more formal education, recent Fraud victims, and individuals inclined to take risks with their financial assets report lower levels of confiden...
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Sociolegal change in Consumer Fraud: From victim-offender interactions to global networks
Crime Law and Social Change, 2005Co-Authors: Kristy Holtfreter, Shanna Van Slyke, Thomas G BlombergAbstract:Advances in technology have transformed Fraud against Consumers from face-to-face, victim-offender interactions to a crime that now transcends international boundaries. Although Consumer protection issues have been of interest to investigative journalists and literary scholars for centuries, the topic has only recently been subject to serious criminological inquiry. Employing the American Consumer protection movement as an historical framework, we examine the evolution of Consumer Fraud. Our review documents that progressive social and legal changes in Consumer protection and corporate regulation, as well as developments in criminological research, correspond to prominent literary exposés of the time. In today's technological age, such a reactive response to Consumer Fraud is neither efficient nor effective. Contemporary criminologists need to simultaneously address the questions of ‘how’ Fraud is perpetrated and ‘why’ it occurs. Toward this end, we identify methodological strategies and data sources to promote empirical and theoretical understanding of Consumer Fraud, and to ultimately contribute to multi-national crime control policy.
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Sociolegal change in Consumer Fraud: From victim-offender interactions to global networks
Crime Law and Social Change, 2005Co-Authors: Kristy Holtfreter, Shanna Van Slyke, Thomas G BlombergAbstract:Advances in technology have transformed Fraud against Consumers from face-to-face, victim-offender interactions to a crime that now transcends international boundaries. Although Consumer protection issues have been of interest to investigative journalists and literary scholars for centuries, the topic has only recently been subject to serious criminological inquiry. Employing the American Consumer protection movement as an historical framework, we examine the evolution of Consumer Fraud. Our review documents that progressive social and legal changes in Consumer protection and corporate regulation, as well as developments in criminological research, correspond to prominent literary exposes of the time. In today's technological age, such a reactive response to Consumer Fraud is neither efficient nor effective. Contemporary criminologists need to simultaneously address the questions of ‘how’ Fraud is perpetrated and ‘why’ it occurs. Toward this end, we identify methodological strategies and data sources to promote empirical and theoretical understanding of Consumer Fraud, and to ultimately contribute to multi-national crime control policy.
Lou E. Pelton - One of the best experts on this subject based on the ideXlab platform.
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How Consumers may justify inappropriate behavior in market settings: An application on the techniques of neutralization
Journal of Business Research, 1994Co-Authors: David Strutton, Scott J. Vitell, Lou E. PeltonAbstract:Abstract Consumer-initiated Fraud is an ongoing problem for marketers. The ability of marketers to combat the problem is undermined by the fact that otherwise principled individuals often selectively engage in Consumer Fraud. The techniques of neutralization (Sykes and Matza, 1957) are investigated as a possible explanation for how Consumers may diminish their perceived guilt for their inappropriate behaviors in retail settings. The techniques of neutralization appear more appropriate as an explanatory framework in situations that involve the unethical disposition, as opposed to the acquisition, of retailing goods. Approaches by which retailers might be able to reduce unethical disposition behavior are discussed.