Big data: is the reinsurance industry ready to harness its potential?

Alex Casey
Alex Casey

Reinsurance has long recognised the importance of data, well before it became a global hot topic. However, as other industries clamber to unlock the competitive advantage so widely promised, has our industry got the appetite and ability to harness the technology and talent of the new data generation?

What does big data mean to reinsurers?

There are a number of reactions that most people take to the term ‘big data’. There’s fear, the worry that everyone else is using it and you’re not; frustration, the idea that the key to future success is sitting on your own servers and no-one can see it; or futility, that it’s too complicated to get your head around and we’ve managed this long with what we’ve got. These aren’t unfounded concerns, especially with declining margins bringing research and development projects under ever-closer scrutiny, but overcoming these hurdles is key to expanding and improving risk transfer as an industry.

The ubiquity and sophistication of third party catastrophe (cat) models in the property reinsurance space has given both our businesses and external investors a growing confidence that reinsurance is on a strong footing when it comes to data. In addition, growing regulation around reinsurers’ views of risk has increased the burden of proof on companies to challenge the output and inhibited many, especially smaller shops, from putting their heads above the parapet.  

However, as reinsurers look to push into new regions and perils and seek increasing diversification, the focus has to return to internal analytics. Although the ‘big data’ techniques of the tech giants may not be suitable or even in scope for most reinsurers, the proliferation of analytics technologies is a game changer for those needing to bolster their own portfolios and handle new risks as they emerge around the globe.

What are the barriers to embracing big data?

Getting a project sponsor on your board who is truly engaged is the first big challenge most companies will face. The industry has a reputation for being slow to adopt change, and investment is tough to support when margins are under pressure, so initial projects should be clearly defined and quickly achievable. An early white elephant project that costs a lot and doesn’t deliver will set a company back years, whereas a staged ramp-up solving well-defined problems has more chance of winning hearts and minds. As investment is normally required over a number of years to build out this capability, board level support is needed to maintain funding for longer-term research and development projects when they arrive.

The second challenge is one of talent to maximise on new technologies. The reinsurance space needs to do more to compete with banking and tech when it comes to attracting the best graduates. The prevalence and breadth of coding talent amongst graduates is much greater than a decade ago and makes them valuable additions for translating real-world problems into digital solutions. In addition, strong leadership and oversight of the technologies employed within the organisation are needed to stop companies tying themselves in knots with incompatible or poorly integrated systems, or investing in the wrong products at the outset.

Lastly, it’s a question of integrating both talent and technology within existing workplaces, and that is perhaps the biggest challenge. Research that exists in a back office benefits no-one unless it can be deployed on the front line. Insights need to be actionable and deliverable in terms of premium and profit, so front line underwriters can recognise the advantage – healthy and constructive scepticism is necessary to the process but should not act as a blocker. For centuries, the best underwriters have been excellent at assimilating ‘unstructured data’ and this is merely an extension of that ability. It is an important one too, if we are to take a less commoditised approach to risk and focus on solutions-led underwriting.

Embracing the benefits

Data analysis should always be a means to make better decisions. Through improved understanding of the pricing on their existing book, expanded product offerings and more efficient deployment of capital, reinsurers should be able to deliver increased shareholder value and improved stability for the financial system. By thinking outside of the box, they can lead their peers and work with the direct insurance market on new and emerging risks to offer creative solutions to complex problems, reduce coverage gaps, and extend the industry’s reach. That’s a good thing, not only for us but for our clients.


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