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Research Proposal On Fraud And It's Different Impacts On Societies And How To Reduce The Number Of Increasing Victims

Credit Card Fraud – Impact on Society and Reduction of Victims: A Research Case Study



Consequently fraud have wide reaching impact, with an estimated cost of $1.1 billion to Australian society per annum (Cuganesan and Lacey 2003), excluding intangible costs, such as lost reputation and invasion of privacy. With heightened awareness of security and privacy issues, identity fraud is receiving increasing attention from business, government and individuals. Fraud occurs when someone gains access to benefits, usually financial, through the use of a false identity as credit fraud linked to identity thieves may gain access to identity information through documents in garbage, direct questioning, stealing records from their employer, or hacking into the organization’s computers and other such examples.

Statement of the Problem

The problem of cheque and credit card fraud has increased in magnitude. Since 1988, British losses from these types of fraud have almost doubled. As consequence, in 1990, total fraud losses were running at £150 million. The problem of uncollectible debt in telecommunication services is addressed by using a goal directed Bayesian network for classification, which distinguishes customers who are likely to have bad debt  (Ezawa and Norton, 1996). Since unsupervised learning does not require a priori knowledge of fraudulent data, it may be used to filter out much normal behavior so that the successive supervised learning processing load is reduced for rule-based system and neural network-based system. Exhaustive rule generation is an interesting issue for rule based approach. The advantage is that the rule-generation step will not lose any of the possible candidates for good rules, and will not require complicated mechanisms.

Purpose of the Study

Fraud implies to negative assumption placing in rigorous impact on society in terms of losses to businesses, government organizations and private individuals. The purpose of research is to recognize impacts of credit card fraud in accordance to society and impose ways to reduce fraud cases and limit the number of possible victims of the situation as well as the need to develop models that include the concept of profiling for credit fraud, and be able to explore how certain  case study organization views fraud and its society based impacts and aspects.

Theoretical Framework

The theory framework will have an importance to credit card fraud research and such process as it will be noted by certain fraud oriented theory and discussions yet there is no conclusive research that focuses on the impact of credit fraud in the society. Theoretical research has attempted to integrate credit card fraud and how to determine victims of the situation and possibly suggest ways to reduce them. The model will adhere to Malakedsuwan and Stevens (2003) model, and represents preconception of the problem domain, there will be an iterative approach in examining the data, refining the model and re-analyzing the data of profiling and interactions


For the research method, there is qualitative approach of the research nature by means of using case study approach that will comprise of semi structured interviews with research participants, human oriented subjects. The research will be conducted with employees from business in banking and finance driven service industry as selected due to the experience in fraud domains and easy access will be made by the researcher.  There will imply to brief interview base outlining the research goals and subject matter for the interview to be given to the participants as prior to conduction of the interview method.  Thus, possible telephone conversation will be in place on the day of the interview in order to clarify discussions and purpose of research. The interviews are going to be in five employees of senior job roles working at the organization’s fraud and security operations area. Interviews will be recorded and then be transcribed to facilitate discussions and analysis. Aside, content analysis are to be used and administered in order to understand data to be gathered as well as collected and such coding can be used in drawing in research paradigms and concepts from noted context formation.


ACCSS 2004 “Australian Computer Crime and Security Survey 2004”, Australian High Tech Crime Commission, ISBN 1-864-99773-7

Bolton R. J. and D. J. Hand. Unsupervised profiling methods for fraud detection. In conference of Credit Scoring and Credit Control VII, Edinburgh, UK, Sept 5-7, 2001

Cuganesan S. and Lacey, D. (2003), Identity Fraud in Australia: An evaluation of its Nature, Cost and Extent”, SIRCA, Sydney

CyberSource company. Credit card fraud management., 1996

De, Krish (2004): “Investigating the Role of Profiling in Detection and Prevention of Identity Fraud”, Research proposal, SISTM UNSW

Ezawa K. J. and S. W. Norton. Constructing bayesian networks to predict uncollectible telecommunications accounts. Ieee Expert-Intelligent Systems &Their Applications, 11:45– 51, 1996.

Malakedsuwan, P., Stevens, K. (2003): A Model of E-Fraud, Proceedings of Pacific Asia Conference in Information Systems, 2003

Stolfo, S. W. Fan, W. Lee, A. Prodromidis, and P. Chan. Credit card fraud detection using meta-learning: Issues and initial results, 1997

Syeda, M. Y.-Q. Zhang, and Y. Pan. Parallel granular neural networks for fast credit card fraud detection. In Proceedings of the 2002 IEEE International Conference, volume 1, pages 572–577, 2002.

Wiedmann, Buxel, & Walsh (2002): "Customer profiling in e-commerce: Methodological aspects and challenges", Journal of Database Marketing, Vol. 9, No. 2, p170–184.




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