Lessons include not blindly jumping on the buzzword bandwagon Pierre du Toit, Head of Technical Pricing & Big Data Analytics, Vitality notes the importance of prioritising the right data projects that are likely to end in driving actual value to your customers and to the wider insurance organisation. "… start small and show the value of data to the company - this way you'll get business buy-in and gradually build momentum over time. Being agile and showing value very quickly is very important for longer-term success within a company."
Other findings were to begin with integration at the front of your infrastructure strategy. Barry Hawkins, Head of Dynamic Underwriting and Pricing, AXA explains: "A comprehensive data source [stores] the data in one place where marketers, pricing professionals and, to some extent, claims analytics can use the same data to drive a single view of customers/ a product/ a portfolio - then you can drive a company-wide strategy."
It is vital to gain a clearer picture of customer lifetime value, Barry Hawkins notes that certain amounts of data are focused on hygiene - whether the client is who they claim to be. For basic pricing, it is important to identify the kind of risks that need to be avoided. Data should produce a lifetime value view of a customer to highlight the high value clients.
No two customers are the same, so why price the same when considering their businesses? Those companies who look at customer lifetime value (CLV) have been shown to be far more profitable than those that don't and big data analytics makes this task far easier than it has ever been.
For the full findings download the article here: http://bit.ly/2hWnbcZ
For more information about Big Data & Analytics for Insurance conference visit https://dataanalyticsinsurance.iqpc.co.uk .
SOURCE Process Excellence Network