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In many customer oriented enterprise environment like banks and retail businesses, data mining business intelligence (BI) performs key functions that enable business organizations determine investment risks and estimate returns on investment. It aids in evaluating the gathered information and presenting them in an understandable and practical design that promote data mining analytics. In the current study, banking and retail services were viewed among the rapidly developing technological industry that maintains significant amounts of electronic data. Handling enormous amounts of transactional data and making choices about risk, client retention, fraud detection and prevention, and marketing management are significant tasks in the banking and retail industries. On the account that fraudsters constantly come up with new schemes and refine their existing schemes so they may avoid being easily identified, it is challenging to identify fraud and prevent it from happening. In order to monitor activities relating to fraud prevention, fraud detection, customer retention, marketing and risk management, business performance, loan classification, and improving customer satisfaction.
About the author
Ugochukwu Okwudili Matthew , Engr Dr. Jazuli Sanusi Kazaure et Dr. Nwamaka Uchenna Okafor sont des universitaires professionnels qui ont de nombreuses années de recherche et d'engagement universitaire. Les auteurs ont travaillé sur plusieurs autres projets universitaires d'importance mondiale.
