Developing an identity fraud measurement model: a factor analysis approach
Purpose – Though many studies and reports have been published about the scale of identity fraud (IDF), no work has been done on developing models to measure IDF. The purpose of this paper is to propose a measurement model for IDF and test the validity of that measurement model. Design/methodology/approach After providing a background on the concepts of IDF, the paper discusses the related term, identity theft. Next, a measurement model is developed, based on the current practice of measurement of IDF in four countries. Exploratory factor analysis (EFA) is used in identifying the indicators and factors of IDF. After the EFA is conducted, confirmatory factor analysis is employed to test the validity of the measurement model. These tests are conducted using the data collected from Canadian financial institutions. Findings The review of the current empirical studies suggests that IDF should be assessed using a measurement model with 33 indicators to measure five factors of IDF. However, the analysis of Canadian financial institutions suggests that a measurement model that includes 27 indicators and four factors is most appropriate for the data. Research limitations/implications The measurement model developed in the present paper is based on an examination of a sample of financial institutions in Canada. Hence, the results of this paper cannot be generalized to organizations in other sectors of the economy. Further studies in other sectors of the economy are required to identify industryspecific measurement model. Practical implications This paper is the first approach toward developing a model for measuring IDF. Originality/value This paper is the first study that attempts to scientifically identify and validate a measurement system in the area of IDF.
|Keywords||Crimes, Fraud, Measurement, Modelling|
|Journal||Journal of Financial Crime|
Miri Lavassani, K, Kumar, V, Movahedi, B. (Bahar), & Kumar, U. (2009). Developing an identity fraud measurement model: a factor analysis approach. Journal of Financial Crime, 16(4), 364–386. doi:10.1108/13590790910993708