Feasibility of artificial intelligence in improving sales and service of insurance agents in the life insurance industry of Malaysia - Fong, Patrick Heng Yin (2023)
Artificial Intelligence (AI) has seen multiple applications across various disciplines, from medicine to strategic business analysis and even home entertainment. The benefits from the application of AI comes from its ability to mimic human cognitive abilities and perform tasks quickly, tirelessly and with almost no errors. While the benefits of AI have been experienced by many industries, however in the context of the Malaysian insurance industry, AI has only even been utilised for back end repetitive processes such as using Robotic Process Automation (RPA) to alleviate the underwriting department or using AI to analyse business information such as claims data or premium rates. As of the time of this paper, there had been no application of AI to support the agents of the insurance industry, and the application of the technology could alleviate the areas of concerns faced by the agency force. In 2020, the central bank of Malaysia or ‘Bank Negara Malaysia’ (BNM) targeted a 75% penetration rate amongst the citizens of Malaysia, however research has shown that the actual penetration was only 41% which is far from the goal that was set by BNM. This is due to the high turnover rate, which is caused by lack of sales volume that contributes to lack of service to insurance policyholders. Therefore, this study aims to explore the feasibility of using AI to assist the agency force and both alleviate their challenges and grow their business in order to not only achieve higher customer satisfaction as well as higher revenue for the insurance companies, but a higher penetration rate which will not only benefit the policyholders themselves, but the country’s economy since the funding of medical services will be paid by private companies rather than on taxpayer’s money which can be diverted to be used for other initiatives that could enhance the economy of Malaysia. Through the use of exploratory, non-structured interviews with candidates sourced through direct contact and snowballing technique, which was analysed using an inductive method following an interpretivism philosophy, in order to develop a theory with a mono-method qualitative approach, adhering to a cross-sectional time horizon; it was discovered that agents understand the qualities of AI and its benefits to their business and their main concerns revolve around the ability of the AI to automate and track their sales and servicing tasks which directly alleviates their challenges, monitoring of sales progress to motivate the agents, leads generation to ensure business and agent longevity in a system that is simple to navigate and easy to understand.