Digital advances, the rise of social networks and the ‘internet of things’ are having a transformational impact on the volume, variety and velocity of data coming at organizations.
While insurers and intermediaries are already very data-driven - capital modeling, pricing, reserving and claims management are all highly data intensive - antiquated systems and siloed cultures make it difficult to collect, store and analyse the seamingly infinit amounts of internal and external data now available. This presents a big challenge as insurers look to become more customer-oriented in product offering and services.
In our recent survey, nearly two thirds of respondents said they still focus on descriptive and diagonistic analytics that provide insights into the past, while just 29 percent say their company uses prescriptive analytics. This is not surprising given the challenges cited above.
Many data strategies fail to deliver as the focus has traditionally been on costly process and technology changes. Now insurers can do these complex projects economically and build an affordable proof of concept. This offers the ability to go beyond predicting future outcomes to using predictive models to dirve action.
We propose an evolutionary approach to data innovation, starting with:
The goal here is to drive actionable insights from observing the business process that bring competitive advantage in a controlled and sustainable way.