商品簡介
However, insurance is an emotion-driven industry. But, (AI) learning system is one machine. How and why can (AI) learning system help human emotion-driven insurance service sale organization to influence insurance clients' emotion to be positive more than negative? It is one interesting question to be explained. When one insurance company grows to mature stage, it won't have effort to make initial steps with chat bots, many have also advanced to robotic advisory. Based on organizational maturity and insurance market also reaches the insurance customer number reducing stage. Due to any country has have many family owns at least one insurance policy. So, it will influence every family's insurance need to be reduced.However, (AI) system new technology is the best method to assist insurers to predict whether who will be the potential insurance customer target groups in order to help the insurance organizations to predict more accurate every family's emotion to find whose unfound insurance needs. As a result, future insurance organizations can apply (AI) learning systems to bring these benefits, they include: attaining rapid growth through channel and potential insurance customer prediction touchpoint of different kinds of insurance need expansion; employing operational intelligent to optimize resource overhead and improve insurance customer new fresh experience insight from (AI) learning system service participation to the insurance organization, modernizing technology to solve legacy problems, such as scalability, service turnaround times etc. So, the most influential advantage is that (AI) learning system can help future insurance organizations to find the best insurance methods to solve insurance customer complains or service challenges. Because insurance is an emotion business, when the insurance client had chosen to buy the insurance firm any kinds of insurance, it does not guarantee that the insurance client has none any complains. SO, the insurance company will encounter reasonable or unreasonable complains often. (AI) learning system's strengths includes that it can find the best method to help any insurance firm to give recommendation to attempt to solve their insurance customers' complains in the shortest time. If the (AI) learning system can really help the insurance firm to find the best methods to solve any insurance clients' complains or enquiries to let every insurance client to feel more acceptable to compare human insurers' insurance customer service feedbacks are more better or satisfactory to let them to feel. Then, I believe that the insurance clients must feel the insurance firm can improve its customer service more efficient and satisfactory. For example, chat bot is one find of insurance product personal financial tracker tool for every insurance customer. Chat bot is starting with a enabled. It is one personal financial tracker and advisor ( starting with a rules-based configuration) to target prospects and insurance customers. Thus, through the use of rules-enables easily configurable decision and process engineers, insurers can not only save on resources, but also ensure more efficient marketing, lead management and insurance sales efforts, all at minimal cost to the insurance company.
