Development of Insurance Suggestion Models and Insurance Robot System based on Customer Insurance Gap

• Main Authors: HSIEH,YI-LING, 謝依齡
• Other Authors: CHIANGLIN,CHIEH-YOW
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/92r532

碩士 === 國立高雄應用科技大學 === 金融系金融資訊碩士班 === 106 === Faced with the rapid rise of fintech, Financial and IT companies have accelerated investment into driving fintech innovations, looking forward to optimize existing business models and service models, or develop innovative technologies to subvert the existing financial business model under the wave of fintech. The fintech that Taiwan actively promotes and develops mainly consists of 5 parts: Big Data, Artificial Intelligence(AI), Robo-Advisor, Biometrics, and Blockchain. However, the current Robo-Advisor only invests in funds and does not completely cover the planning scope of financial products, especially the personal insurance product planning section. This research built an Insurance Robo-Advisor in the spirit of Robo-Advisor. Hoping that insurance demanders can interact with the system, starting from demander’s insurance gap, to find out the cheapest insurance suggestion that can make up for the demander’s insurance gap. For this reason, this research develops different insurance suggestion models. We started with making up for the seven major insurance gaps by insurance products provided by different insurance companies, and then, sequentially considered different insurance suggestion models such as insurance principal contract and attached contract synchronous planning, budget limitation, importance of insurance demanders gap, and individual insurance contract features. In order to prove that the insurance suggestion model could indeed be implemented in the system, we developed an “Insurance Robo-Advisor” system based on the insurance suggestion model, and completed the insurance demand analysis and finally provided the best insurance suggestion products in sequence. Finally, we discussed what kind of extended application features might be necessary in the self-service insurance suggestion system. Insurance suggestion business models can then be developed based on this research.