Insurance intelligence provider, Percayso Inform, has been selected to be part of the fourth cohort of Slaughter & May’s Fast Forward emerging tech entrepreneur’s programme. Whittled down from hundreds of applicants, Percayso Inform was one of five diverse businesses to be selected, chosen for its innovative approach, its point of difference in its market, and the strength of its ambition.
Partner and Fast Forward co-lead Rob Sumroy explains: “In each Fast Forward cohort we’ve sought out the best, brightest and most innovative businesses. All five of our chosen cohort members have incredible potential. It is exciting for us to help businesses such as these grow and succeed.”
Ben Kingsley, partner and Fast Forward co-lead, continues: “We’re really looking forward to working with businesses like Percayso, pushing boundaries in data analytics. Our diverse cohort is testament to the pioneering and inventive mindset of the current generation of entrepreneurs, and I am pleased that we are able to support each of them at this key stage of their development.”
As a member of the Fast Forward cohort, Percayso Inform will be offered £30,000 of value-add services from Slaughter & May including legal advice.
Rich Tomlinson, Managing Director of Percayso Inform says: “We’re absolutely thrilled to be chosen by Rob and Ben to become a member of their Fast Forward programme. We’re passionate about bringing the next generation of insurance intelligence to insurers and brokers and firmly believe our capabilities can make a massive difference them. Being selected from such a talented pool of diverse businesses is, in my view, a significant independent endorsement for the approach we’re taking.”
Percayso Inform launched its next generation insurance intelligence platform at the beginning of the year. Harnessing the very latest techniques in data science and machine learning, allied with new powerful datasets enabled through a combination of GDPR and consent driven customer journeys, Percayso Inform can deliver up to an eight-fold improvement in predictive power
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