For instance, in the case of car insurance claims, AI can be used to instantly detect the extent of damages by analysing the photographs uploaded by the car owner. Insurers today leverage Artificial Intelligence ( AI) technology, along with Machine Learning and advanced data analytics, to accurately measure the extent of liability and also to predict collusion and potentially fraudulent claims. Albeit in nascent stages, such tech implementations are sure to revolutionise the customer experience in insurance. On the global front, some insurance companies have introduced AI-enabled voice assistants and video call assistants for consumer support. Backed by cutting-edge technologies, these chat-bots answer queries like a seasoned customer-care executive. AI-powered chatbots are already answering queries of customers round the clock with zero-wait-time. Technology today makes it possible for insurance companies to use AI-enabled automatic claim processing to substantially reduce the turnaround time from weeks to days to hours, and even to minutes. This also distinguishes a good customer experience from a bad one. Historically, one of the biggest pain-point for consumers of insurance products has been the claim settlement process. This makes it possible to offer lower premiums to those who maintain a healthy lifestyle by eating healthy, exercising daily and getting regular medical check-ups. ![]() For instance, instead of just using the age and medical history of a customer to calculate the risk in providing them health insurance, it is now possible to take into account their lifestyle and even their vulnerability to diseases in future. Since insurance essentially means paying to cover the risk, the use of big data can help deliver insurance products at fairer premiums by accurately identifying risk for each consumer. Using Big Data Analytics to Arrive at Fairer premiumsĭrawing from the individuality of consumers, it is safe to say that just like their needs, the risk value is also different for different individuals. This information can be used then in any follow-up conversation across any platform to offer a highly personalised experience to the customer. Data such as real-time events and customer interactions – like payment, booking, ticket, call and browsing activity – can be used to create a 360-degree profile of the customer. This can be achieved by using technology to remember the context of the conversation, and even predicting the context upfront right when the interaction begins. What this typically means is that the customer has to be the primary focus irrespective of which platform they use to interact with the business. This is the other side of offering personalized products and services. The idea is to respect the diversity of the consumers and treat them as independent individuals by offering them unique insurance products to suit their specific needs.Įstablishing the context in the customer journey Many insurers globally are using data accessed from wearable fitness trackers, cell phones, home automation devices and even refrigerators to offer personalised products. ![]() Since no two individuals are exactly alike, why should the products being offered to them be? With the emergence of big data analytics, it is now possible to use data from several sources to accurately identify a prospective consumer and offer personalised and tailored insurance products to suit the needs of a diverse consumer base. ![]() They have enabled insurers to reach out to the untapped sections of the nation, fuelled by the increasing penetration of smartphones and high-speed Internet in the tier-II and tier-III cities of the country. ![]() Digital payment has been the foundation on which the whole structure of the digital onboarding process stands.
0 Comments
Leave a Reply. |