Chatbots and Conversational AI in Retail Banking: Transforming Customer Experience and Service Efficiency

Abstract: The evolution of Chatbots and Conversational Artificial Intelligence (AI) is set to redefine customer engagement in the retail banking industry, driving improvement in service delivery as well as operational efficiency. This report examines how conversational AI technologies – driven by natural language processing (NLP), machine learning (ML) and speech recognition – can help banks provide personalized, real-time and scalable Customer service. AI chatbots have automated transaction-biased tasks such as balance checks, transferring of funds, applying for a loan and settling a complaint to minimize manual involvement while increasing the level of accuracy and speed of response. What’s more, sophisticated systems such as generative AI and context-aware dialogue engines now replicate human-like interactions, increasing customer satisfaction and engagement on the go across a range of digital channels. Studies also show that chatbot applications can accelerate a process while at the same time gathering important customer information to be used in predictive analytics, cross sell and risk detection. But the emergence of conversational AI face many challenges such as privacy and security, bias in algorithms, the need for emotional intelligence. The study recommends that a human–AI hybrid model to be adopted for seamless integration of AI chatbots to retail banking, where empathy, transparency and ethical governance in customer relationships are nurtured.

Keywords: Conversational Artificial Intelligence, Retail Banking Customer Service, Natural Language Processing (NLP), AI Chatbots and Automation, Human–AI Hybrid Interaction Model.