Taking steps towards a data-led insurance industry

Magdalena Ramada from Willis Towers Watson explains that while many large underwriters and reinsurers started their big data and predictive analytics journey over a decade ago, most midsize and smaller insurers have only just begun

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By Guest on 31 October 2017
Taking steps towards a data-led insurance industry

This article first appeared in the Autumn 2017 issue of The Record.

How insurers collect unique data sets will be key in a more connected world. Smart, -value-adding apps and the design of products and services that, by their very nature, generate lots of useful insurance and customer behavioural data, will underpin insurers’ attempts to gather unique data sets. This can help them learn more about customer needs, allow them to get closer to their customers and facilitate a new type of relationship that will shift from low frequency to a high frequency interaction, allowing for better near real-time risk mitigation. However, it will also have very broad implications for the likely volumes of data to be gathered and processed.

Some companies have already started to store big data – both structured and unstructured – in data lakes, instead of simply organising them; they are then using technology to access and interrogate their data. Results have, in some cases, been impressive. Still, there is much to be done in this area.

Regardless of the speed at which insurance technology and data analytics innovation occurs, the future of insurance is very likely to be one in which the nature of risk, the value of data and the relationship between underwriters and customers is radically changed. The impact will be felt on products and distribution channels, customer and risk models, regulatory frameworks, and the transition into cognitive big data and next-generation predictive analytics.

Like any other transformation, this requires strategy and direction, crucially underpinned by company views of the future state – despite the many uncertainties and out-and-out unknowns. Just as important is where the company fits into those future states, the associated implications for data and analytics, risk appetite, talent retention and attraction, customer relationships, market positioning, cost-efficiency, and the required levels of innovation and change.

Transformation won’t happen overnight, but has to start somewhere and incorporate longer-term scenario and contingency planning. Subsequent practical steps to kick-start programmes include looking at a foundation-level data infrastructure that is or will be in place and a corporate culture that understands the value of data and enables innovation. It’s also important to implement a joined-up approach to opportunities and initiatives. Lead by doing, as it will give insight, aid recruitment and retention, and may be the source of some lasting competitive advantage.

There is general agreement that companies best able to ride the disruptive wave of insurance technology are highly agile, geared to execute managed ¬risk-taking activities/investments, quick to make major decisions and are capable of forming strategic partnerships when advantageous.

Magdalena Ramada is senior economist at Willis Towers Watson

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