Improving Customer Trust through Fraud Prevention E-Commerce Model

Subscribe to access this work and thousands more

The advancement of E-commerce brings trust concerns in society, due to the lack of physical inspection of items by customers. Online fraud is badly menacing the customers and e-commerce boom in society because E-commerce has removed the barriers of physical contact between merchants and customers in the business environment thus making the online transaction to be vulnerable. This has brought some challenges and of most importance is customers’ trust amidst fraudulent transactions. The problem of customer trust due to fraud has mandated greater cooperation between organizations and customers to enhance trust. In this paper, a Multi-Authentication E-commerce (MAE) system that uses rule-based methods and distinct checks to prevent fraud from false virtual stores, thus enhancing customers’ trust, was designed using a Java card fraud detection framework, configured rules, customized filters, and tools, to achieve high rates of fraud prevention. This model uses a centralized merchant registration retrieval (CMRR) system to ensure efficiency, accuracy, and comprehensive customer fraud prevention and support. The MAE model was tested and evaluated using multiple regression analysis on the data generated on IBM SPSS 2.0. The result revealed that customer trust is guaranteed and enhanced in the MAE model because fraud is prevented when the merchant’s location is verified. The CMRR component can guarantee merchant integrity. The evaluation of the parameters used in the data analysis of the structured questionnaire showed that customers’ trust is dependent on fraud prevention and trust is enhanced through the use of CMRR for fraud prevention in online transactions. In future, another algorithm can be combined with rule-based technique to counter new fraudulent actions as it will enhance the efficiency of the CMRR.

Subscribe to access this work and thousands more