Framework for Detection of Fraud at Point of Sale on Electronic Commerce sites using Logistic Regression

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Abstract Many businesses have been positively impacted by electronic commerce (ecommerce). It has enabled enterprises and consumers to transact business digitally and experience diversity as long as the internet can be accessible and a gadget to surf the internet is available. Several governments have gradually adopted electronic payment throughout the country. The Nigerian government has also done a lot of prodding toward the adoption of a cashless economy, which includes embracing ecommerce. As ecommerce expands, so does actual and attempted fraud through this channel. According to the Nigerian Central Bank, electronic fraud would reach trillions of Naira by 2021. The purpose of this work was to employ logistic regression as a decision-making tool for detecting fraud in e-commerce platforms at the point of sale. The main contribution of this research is a model developed using for detecting fraud at the point of sale on electronic commerce platforms. The accuracy of the result is 97.8 percent. The result of this study will provide key decision makers in ecommerce firms with information on fraud patterns on their ecommerce platforms, this will enable them take quick actions to forestall these fraudulent attempts. Further research should be carried out in developing countries.

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