Sentiment analysis has transformed into one of the banking industry’s most cutting edge instruments that organizations use to decide how they should respond and focus on consumer remarks. This detailed technical review explores the use of sentiment analysis systems in the banking sector, probing into the complex framework required to efficiently implement these systems. The real first-mover advantage banks will be able to make the most of right out of the gate is improving customer experience, as banks will more easily be able to deploy automated response systems and process feedback in real time, all made possible through the combination of advanced machine learning and natural language processing capabilities. The implementation has a number of clear limitations, such as enhancing sales reliability, advancing mobile banking and customizing the price framework. This new custom armature is a response to massive data security, system integration and accuracy preservation gaps, while introducing automated point production, dynamic precedence management and predictive analytics. These quantitative results demonstrating deeply profound improvement in NPS, functional performance and product development cycle times underscore the tremendous effect sentiment analysis as a component of AI innovation has on digital-first banking.
Naveen Kumar Chandu (Mon,) studied this question.