Digital technology, big data and the mutual sector

Mutual and cooperative insurers have justifiable pride in the high levels of service they offer to their members. But, with improved and deeper customer relationships being a key focus for the commercial sector’s application of technology, should they be taking steps to repel the threat to even long-held customers’ loyalties?

For most commercial insurers, customer relationships and the customer value proposition are key potential applications for big data and analytics. This has significant implications for mutuals and cooperatives that, for decades or sometimes centuries, have typically been in the ascendancy over customer service and satisfaction levels.

Customer relationships and the customer value proposition are key potential applications for big data and analytics

But if an insurer, or increasingly a specialist InsurTech business, can entice mutual customers with an insurance offer, or perhaps a packaged set of offers, that are closely tailored to their employment, lifestyle, interests and budget, heads might well be turned. And probably more so, if insurers further present such offers using some of the techniques perfected by the new generation of online retailers and technology specialists, so that customers can have real time service, earn relevant rewards or incentives, or are directed to partner sites that may also interest them.

For most, this is still an ambition rather than a reality, often thanks to embedded business cultures and/or a complicated web of legacy systems that hinder progress. Equally, it’s not beyond their reach.

Digital crossroads

How then might the mutual sector respond and make its own better use of available and future technological innovation, bearing in mind that many mutual and cooperatives are, by nature and tradition, quite conservative organizations, and this often extends to the application of technology?

Enhanced models and analytics can be valuable tools for optimizing the less varied sources of capital available to mutuals

First, it has to be acknowledged that some larger organizations are already well into their stride and quite sophisticated in their use of technology and analytics in pricing in particular. Others, however, are barely out of the starting blocks. And, if anything, legacy systems typically make mutuals even more reliant on the skills and knowledge of their people than the non-mutual sector.

Yet, well-targeted investments in technology, data and analytics capability certainly have the potential to help mutuals. In terms of cementing prized customer relationships, using data enrichment and analytics to fill in gaps in understanding of members could potentially help better wrap policy offerings to serve members’ interests or to determine whether product diversification could attract new members – and not alienate existing ones. Enhanced models and analytics can also be valuable tools for optimizing the less varied sources of capital available to mutuals, including reinsurance.

Charting a course

Any transition can be made more manageable by pinpointing the data and the actionable analytics required to achieve the identified business objectives

Inevitably, such objectives could test existing IT infrastructures – but the cloud and other on-demand sources of processing capacity can provide viable options nowadays. Moving forward effectively will also likely require some people and cultural shifts to make the most of investment in this area, because digital effectiveness doesn’t hinge on fancy websites or portals, but on coordinated back office operations. At the same time, any transition can be made more manageable by pinpointing the data and the actionable analytics required to achieve the identified business objectives. For example, rather than scouring the data universe from the outset, untapped sources of internal data often have considerable value.

Whatever the objective, it’s worth remembering three important pointers for technology and big data initiatives in any insurance organization.

Use cases, not technology, should lead the way. Quick wins are vital in proving the value of investment in big data and analytics. Whatever insurers do, particularly in the early stages, should be driven by finding nuggets of value for the business, not what technology will be needed down the road.

If you’re going to fail – fail fast. Focus limited analytics resource on projects that have a future.  This avoids spending weeks, or months, developing a capability that tests stakeholders’ patience and that may not even work out as intended.

Involve subject matter specialists. Appropriate leadership of specific use cases is essential. That means that an underwriting use case should be led by an underwriting expert, who can determine whether insights that may look valuable are actually useful, leaving analysts to focus on the technical response. Equally, they can advise on whether an initiative is practical and implementable at the coal face.

Amid the widespread digital disruption going on within the insurance industry, the mutual sector has generally earned something of a head start in its customer (member) relationships. Judicious investment in behind-the-scenes digital and analytics capability could help retain that advantage and open up new avenues for business improvement.

About Robin Swindell

Robin is Executive Vice President & Regional Director of Willis Re. Robin works in the London office as part of…
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