The current new ‘hype’ within the insurance industry is both big data and automation. Yet, such a move towards adopting the new tools of this Internet of Things (IoT) era, brings both risk and opportunities. On the surface, it seems the insurance industry is rushing to embrace this new era as identified by the recent implementation of Blockchain in Maritime insurance or is it?

For when we look beneath the headlines, it seems the industry is far from embracing this change that could bring $243 billion to the industry according to Capgemini. Yet, despite the clear benefits, insurers are still unsure. Why is that?

This was answered in a new report from Capgemini, “Growth in the Machine: How financial services can move intelligent automation from a cost play to a growth strategy”. The report, which surveyed more than 1500 financial services executives globally, including more than 500 in the insurance industry, brought up some interesting statistics.

For insurers, the largest concentration of automation occurs within Policy and Servicing along with Compliance (10%) with Products (9%) in a close second. So, despite the recent rhetoric, the industry is not chugging full-steam ahead with automation, as showcased in the reservations expressed by insurance executives about this burgeoning technology. Many struggle to make a business case for it and some have technology concerns too, such as privacy and security (48%) and systems-integration (48%) issues.

So, clearly, the industry is not running headless into the bright lights of the future. Far from it; it seems (re)insurers are prudently questioning why they need to invest wholeheartedly in the process of automation and on a wider scale, the Internet of Things (IoT).

As Russell Group has been arguing consistently over the last year or so, the right approach is not the quantity of data provided by automation but the quality of data. In tandem with this approach, we need to build an integrated business model to process and use the data. Only when insurers complete both steps: developing quality data and integrating their business models can they truly automate their process and turn the risks of the Internet of Things (IaoT) into abundant opportunities.