AI-Driven Customer Behavior Analysis in Banking
Abstract
In the modern world where feedback is the most valuable part, data generation for customer feedback is an everyday job. Users should not underestimate the importance of having feedback from bank customers. The banking sector is one of the fields where Customer Relationship Management (CRM) is necessary. CRM is the foundation for customer satisfaction, retention, and loyalty, and a prerequisite for successful relationship marketing. The success of a business in the banking sector is mostly connected to the satisfaction of its customers, as customers are the most important resource, and they should be aware of their value to the business. This study aims to provide banking sector firms with helpful insights to create better business plans while using new data analysis techniques by creating recently developed risk indexes. The age of Big Data starts when part of the overall data is structured while the majority remains unstructured. The largest portion of this data is generated from users, and banking will not only collect feedback based on the products they offer. As models show trends in the big data sector, it is evident that these models can be used to increase data quality and business outputs. The most expanded areas where models are being applied are banking, fintech, and customer feedback sentiment analysis.
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