Evaluating AI Accuracy and Precision Using Artificial Neural Networks in the Banking Sector

The integration of Artificial Neural Networks (ANNs) in the banking sector has contributed significantly in enhancing the accuracy and precision of AI driven decisionmaking processes. A major advancement in this segment is the use of facial recognition technologies that provides additional layer of security by authenticating the users and planting on the various transactions. Facial recognition technology aids in identification of customer behavior patterns. As the banking sector faces persistent challenges of fraudulent and operational inefficiencies there is a need for advanced technological solutions. AI powered facial recognition systems enables real time behavioral analysis that helps in identifying unusual patterns of indicative fraudulent activities. The study proposed a conceptual framework that aims to detect and reduce the occurrence of frauds and errors by the integration of AI and multilayered blockchain technology in the banking system. The paper proposes an approach for banks to use the ANNs in identifying customer behavior and develop competencies and strategies of building strong customer relationship management. The study contributes to the ongoing discourse of AI-driven banking solutions through ANN-based model to develop core strategies for robust security mechanism.