Insurance Veteran Kevin Sinclair Joins Earnix’s Advisory Board
London, England (PRWEB) May 13, 2008 – Kevin Sinclair, an insurance veteran with a track record of over twenty five years of industry leadership, has joined the advisory board of Earnix, a leading provider of customer value and price optimisation solutions for insurance and banking.
Mr. Sinclair has recently assumed the position of Managing Director with rapidly growing underwriting agency iPrism. Founded by well-known insurance professionals, iPrism offers brokers an alternative channel for commercial lines SME business. Prior to joining iPrism, Mr. Sinclair was Managing Director of AA Insurance, Great Britain’s largest independent home and car insurance broker, prior to the company’s £6bn merger with Saga. Previously, Mr. Sinclair held various posts including Director of Marketing and Underwriting at AXA and Director of Underwriting at Guardian Direct.
“The addition of Kevin Sinclair to the Earnix advisory board brings a significant contribution to our industry depth and knowledge,” said David Schapiro, Earnix’s Chief Executive Officer. “Kevin’s business acumen and his background with both underwriters and brokers will undoubtedly provide Earnix with valuable input that can only come from an industry insider.”
“In an insurance market marked by commoditization, optimisation technology is absolutely critical,” said Mr. Sinclair. “The companies that are best at pricing will be the ones that win. Moving forward, it is going to be very difficult to compete in this market unless you have the right technology in place. Earnix brings genuine innovation to the insurance marketplace, with a leading technology that every insurance company should be aware of. I look forward to the opportunity to work with the Earnix team.”
Earnix provides an advanced analytics platform designed for the financial services industry, which integrates real-time decision-making capabilities into the business process, delivering significant results.
Earnix’s modeling, algorithms, and Machine Learning capabilities automate the rapid deployment of customer-centric offers by considering variables such as price, product features, and distribution channels, to optimize KPIs such as revenue, profit, sales volume, and customer satisfaction.
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