A Design on Bank Customer Complaints Analysis using Natural Language Processing

The banking sector has undergone a major revolution with the advent of digital transformation. The entry of Fintech and tech giants such as Google, Amazon, and Facebook have introduced convenient banking that is easy to understand and use. In this focused condition, banks are understanding the significance of client care and fulfillment and need to give close consideration to the Voice of Customer to improve client experience. By dissecting and getting bits of knowledge from client input, banks will have better data to settle on key choices. In their quest to better understand their customers, banks are seeking artificial intelligence (AI) solutions in the form the of sentiment analysis. What is sentiment analysis? In simple words, sentiment analysis is the process of detecting a customer’s reaction to a product, brand, situation or event through texts, posts, reviews, and other digital content. Using sentiment analysis, business leaders can gain deep insight into how their customers think and feel. The analysis can help in tracking customer opinions over a period of time, determine customer segmentation, plan product improvements, prioritize customer service issues, and many more business use cases