Objetivo
The world is shifting to a new business model, were customers have changed their purchasing path: they are happier subscribing to the outcomes they want, when they want, rather than purchasing a product with the burden of ownership. Consumers today have new expectations; they want to achieve outcomes, not ownership; customization, not generalization. The car insurance market is traditionally linked to the old bonus-malus model, a system that penalizes the ones who make accidents and rewards those who do not incur in them. In a consumer oriented world, insurance becomes a tool for the driver and not just a mandatory cost. What do you think about a relevant cost reduction (up to 40%) but also an added value according to driver behaviors? And what about a system connected with your necessity? A free coffee when you are tired? Gasoline discounts? A free coverage for your weekend because you are a good driver? FAIR meets such requirements, developing a cloud-based ecosystem to commercialize big data and machine learning based insurance, turning customers into subscribers. The coordinating partner in cooperation with an insurance broker and a multimedia company is launching an on-demand insurance service for connected cars. The new insurance policy is revolutionizing the traditional sector with a Pay-Per-Mile and Pay-how-you drive approach, introducing access to discount/cash back opportunities, setting-up and managing insurance packages via app and accessing new safety and reporting functionalities. The new model will be coupled with a service for car dealers and fleets that will bring advantages in terms of car health remote monitoring, knowledge of customers’ experience and advertising tailored service. The competitive advantages: superior risk selections and loss control; analytics to support digital underwriting process through a war room based on driving and crash data; better pricing and cost claims reduction and reporting functionalities to government facilities.
Ámbito científico
- engineering and technologyenvironmental engineeringenergy and fuelsliquid fuels
- natural sciencescomputer and information sciencesdata sciencebig data
- social scienceseconomics and businessbusiness and managementbusiness models
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationsmobile phones
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Programa(s)
Tema(s)
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-SMEINST-2-2016-2017
Régimen de financiación
SME-2 - SME instrument phase 2Coordinador
20124 MILANO
Italia
Organización definida por ella misma como pequeña y mediana empresa (pyme) en el momento de la firma del acuerdo de subvención.