Time taken to deploy new pricing models is too long. Several insurance companies battle with the inability or delay in using new data sources in pricing. There is a need for accurate pricing models that can be rapidly deployed and use new data sources that become available and maintain accuracy over time.
French mutual insurance company, Covéa, faced their own challenges. They needed a platform that supported building models on a very large data set. They also wanted to deploy those models and score incoming quotes in real-time. Thankfully, machine learning was able to improve the speed of modelling and give them the opportunity to handle more than 10 million quotes a month. But, in a crowded aggregator led market – is there room to improve pricing competitiveness? How can you improve business continuity by leveraging cloud? How can you outpace and outprice the competition with machine learning?
Join Demarq and a select group of industry experts to discuss the challenges facing the insurance industry and how delivery of new pricing tools to a cloud first architecture can help business continuity.