Artificial Intelligence and  NLP -Based  Chatbot for Islamic Banking and Finance

Literature Review  

Till the expectations from investors will keep growing, the use of artificial intelligence (AI) and natural language processing (NLP) will keep on growing in various domains. Banks, financial institutions, investment brokers, and mutual fund agents are using AI-powered chatbots for the hassle-free customer experience for advising customers and giving them financial advice in the most innovative way (Rabbani 2020b). Chatbots have been the most hyped application of NLP and AI in the last few years (Robert, 2016). Natural language processing is one of the most prevalent research areas nowadays. NLP and AI have been used in a variety of application areas such as sentiment analysis (Astya, 2017, Goyal, 2016), wind speed forecasting (Bali et al, 2019, Gangwar et al., 2019), smart meter load visualization (Kumar et al, 2020), question-answering, information extraction, and machine translation (Shahnawaz, 2011), etc. Many different types of approaches have been applied from processing natural languages such as the Bayesian theorem based statistical approach (Shahnawaz, 2013b), artificial neural network-based approach (Mishra, 2012, Khan, 2011, 2019), and case-based reasoning-based approach (Shahnawaz, 2015) and many more. A variety of approaches has also been applied in other issues related to NLP such as handling case markers in machine translation output (Shahnawaz, 2013a), addressing the issues of translation divergence patterns in machine translation output (Khan, 2018), etc.