Gartner Symposium is so focussed on the technology that drives business success that it can sometimes be easy to lose oneself in the excitement of new innovations, and forget about the real industries which count on technology for their success. One industry however, was certainly not possible to forget about, and that is insurance.
Insurance, reinsurance, broking and underwriting between them comprise an appreciable chunk of the financial services sector in many countries, including the UK, and collectively underpin the operational risk profile of global trade. Directly and indirectly, they also shore up vast swathes of the consumer and investment finance industry in the developed world.
A more efficient insurance industry is in everybody’s interest. But insurance as a sector has been slow to take advantage of technology to increase the performance of its products and overall business model. In banking, the blossoming of the fintech sector has been followed by an equally vigorous adoption of both customer-facing and backend technologies by the established financial services players. However, there has been no comparable activity in insurance, either by the industry or by third party innovators. Insurance was one of the first industries to adopt consumer-facing price-comparison websites but, this appetite for innovation has not extended to technologies supporting the actual running of the business.
That seems particularly remarkable when one considers the sheer complexity of insurance companies’ business models. One eye-opening statistic quoted at Gartner was that 93% of insurance companies do not use information to spur innovation. Furthermore, only 14% of insurance CEOs believe that their business effectively monetises its data.
Now, many CEOs would think of that as meaning the analysis of customer data – but there is a whole avenue of analytics that is even more rarely exploited. Regulatory and operational requirements mean that insurance companies maintain financial data sets that are exceptionally detailed, accurate and rich. That data can be used to inform operational and financial management on a daily basis, and drive business performance.
For example, with connections to all the relevant sales and market data, a relatively simple mathematical model can define all the factors affecting margin on a specific product, and isolate those that can be controlled from within the business. Viewed as a set of variances, it is then possible to see whether the business is doing everything it can to protect its margins and, if not, to identify the actions needed to do so.
If that model is constructed as part of a larger map of value drivers across the business, it is then possible to accurately assess the influence of such single factors on the wider organisation, and to create robust predictive analyses covering possible regulatory, market and economic scenarios. That offers a view of risk and opportunity that is much more dynamic, and responsive to market conditions than anything currently in use at the vast majority of leading insurance companies. It also offers the prospect of genuine competitive advantage for those willing to adopt this approach to driving business performance.