This report presents a research proposal focused on the prediction of financial fraud using data mining techniques, specifically the logistic regression model. It begins with a literature review highlighting the prevalence of financial fraud and the effectiveness of data mining in identifying and mitigating such risks, referencing key studies on bank fraud and financial statement fraud. The review emphasizes the importance of data mining in detecting fraud signals and protecting sensitive user data, and the use of automated fraud detection systems. The research methodology outlines the inductive research approach, qualitative research design, and a literature review strategy for data gathering. The data analysis will employ descriptive content methodology to analyze the gathered information. The proposal aims to develop a self-adaptive framework, implementing automated fraud detection mechanisms using intelligent feature selection and machine learning techniques to enhance the security of financial systems and consumer data.
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