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Why have insurance companies been slow to adopt digital twins?




Insurance companies have been slower to adopt digital twins than their counterparts in other industries. Accenture’s research, Technology Vision for Insurance, indicates that only 25% of insurance executives are experimenting with the mirrored world and digital twin technology, although 87% agree that these technologies will be crucial to working together in the ecosystem partnerships needed for long-term success. . Why have so few insurance companies taken the step?

There is inertia around products and pricing

Using digital twin data, including streaming data and real-time risk data, means changing the way products and offers are priced. This goes against 200 years of actuarial sciences based on collecting data, assessing risks and building insurance products that insure the masses. Although we have seen a proliferation of use-based products in personal lines for cars over the past decade, with some operators reaching a meaningful scale, I think the scale is the exception and I wonder how much of the captured telematics data really finds its way into pricing algorithms.

Computer platforms and data patterns are often too heterogeneous to provide meaningful insights

A certain scale of homogeneous data is required to be able to draw material conclusions. In personal auto lines, for example, if you retrieved telemetry data from a Toyota black box, you may well be able to use that data efficiently. Because there are so many Toyotas on the road, one can draw broad conclusions from it. In addition, in a world of personal transportation, the data volumes and behavioral characteristics of that risk are quite homogeneous, so insurers can develop new products and pricing with confidence.

But for home insurance companies that refine their offerings for affiliated homes, it can be more difficult. The types and maturity of instrumentation vary widely, as do the data sets, depending on whether you are looking at data from Google maps, Amazon devices, ADP security systems or building management systems for commercial real estate. The same applies in the various industries that insurance companies serve. The data payload can vary greatly between public units, transport units and manufacturing facilities, for example.

Still, digital twins offer valuable opportunities

Despite these obstacles, I believe the real benefits of digital twins are worth the effort for insurance companies. More data from a range of sources combined with analysis and AI can offer a variety of opportunities to reduce costs, increase revenue and provide customers with better service.

In my next post, I will look at four areas where there is potential for you to make profits if you implement intelligent digital twins.

In the meantime, if you want to learn more about the technology trends that are expected to affect insurance companies, read our report: Technology Vision for Insurance 2021


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Disclaimer: This content is provided for general information purposes only and is not intended to be used in consultation with our professional advisors.


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