TY - THES ID - 148641670 TI - Developing a scalable business model in the insurtech market based on Machine Learning model. AU - Dezza, Samir AU - Blavier, André AU - Denis, Pascal AU - Paeschen, Julien PY - 2019 PB - Liège Université de Liège (ULiège) DB - UniCat KW - Fintech KW - Insurtech KW - Artificial Intelligence KW - Startup KW - Internet of things KW - Business Model Canvas KW - Sciences économiques & de gestion > Stratégie & innovation UR - https://www.unicat.be/uniCat?func=search&query=sysid:148641670 AB - The purpose of this thesis is to understand the particularities of the business model used by start-up in the insurance sector. During the various chapters, the reader will be able to discover a sector that is at the gateway to a transformation of its current functioning. Forced to adapt to new disruptive elements, insurers as we know them find it difficult to be as reactive as start-ups. These disruptive elements are supported by the development of technology and artificial intelligence.

Can we develop an effective insurance business model in Belgium? What can Machine Learning models bring? These are the questions we will ask when we observe different innovative players in the market. During this thesis, we will study what new technological models bring to the different levels of the insurance value chain.

This thesis also gives a complete description of a new phenomenon in the insurance sector: Peer-to-Peer insurance. Part of this study focuses on the classification of these new types of insurance and examines their benefits. This detailed overview is then accompanied by an analysis of the disruptive elements that lead to the emergence of new business models.

The central element of this transformation concerning technology, this thesis attaches great importance to it. First of all, the theoretical aspects of Machine Learning were studied and secondly, the practical application led to the development of an analysis of a Business Model Canvas. ER -