AI Based Banking Enterprise Solution Using Related AI-Agent, Prediction of Customer with Fraud and Churn

Artificial intelligence is reducing manual work significantly. Artificial intelligence can be used in different fields, but in our application, artificial intelligence is used for banking Agentic applications as well as customer fraud and churn prediction. Natural language processing (NLP) and machine learning classifiers are used for AI-Agent based applications with higher accuracy compared with state-of-the-art techniques. Proposed application even used for financial risk prediction using different machine learning algorithms. To understand the customer behavior based on customer input data and finding customer churn is also included as additional. The proposed method uses different machine learning and deep learning algorithms for the proposed AI-based application. Performance analysis of different machine learning and deep learning algorithms is calculated using different metrics such as accuracy, precision, recall, and F-score. From multiple algorithms, the algorithm that has higher accuracy is considered for further prediction in the specific application. In the banking enterprise solution, these types of artificial intelligence-based applications are used as advancements and to retain the customers.