Other parts of this series:
Insurers have been slower to adopt digital twins than their counterparts in other industries. Accenture research, Technology Vision for Insurance, suggests that only 25% of insurance executives are experimenting with the mirrored world and digital twin technologies, even though 87% agree that these technologies will be essential for collaborating in the ecosystem partnerships required for long-term success. Why is it that so few insurers have made the leap?
There’s inertia around products and pricing
Using digital twin data, including streaming data and real-time risk data, means changing how products and offerings are priced. This goes against 200 years of actuarial sciences based on pooling data, assessing risk and building insurance products that insure the masses. While we’ve seen a proliferation of usage-based products in personal lines auto over the last decade, with some carriers achieving meaningful scale, I think that scale is the exception and wonder how much of that captured telematics data is really finding its way into pricing algorithms.
Data platforms and data patterns are often too heterogeneous to provide meaningful insights
It takes a certain scale of homogenous data to be able to draw substantive conclusions. In personal lines auto, for example, if you pulled telemetry data from a Toyota black box, you might very well be able to make effective use of that data. Because there are so many Toyotas on the road, you could draw broad conclusions from it. Furthermore, in the world of personal transportation, the data volumes and behavioral attributes of that risk are quite homogeneous, so insurers can develop new products and pricing with confidence.
But for home insurers refining their offerings for connected homes, it could be more difficult. The types and maturity of instrumentation vary widely, as do the datasets, depending on whether you’re looking at data from Google maps, Amazon devices, ADP security systems, or the building management systems of commercial properties. The same is true across the various industries that insurance carriers serve. Data payloads could vary wildly across public entities, transportation entities and manufacturing facilities for example.
Nevertheless, digital twins offer valuable opportunities
Despite these hurdles, I think the very real benefits of digital twins are worth the effort for insurers. More data from a range of sources paired with analytics and AI can offer a wealth of opportunities to reduce costs, grow revenue and provide customers with better service.
In my next post, I’ll look at four areas where there’s potential for you to make gains if you implement intelligent digital twins.
In the meantime, if you’d like to learn more about the technology trends expected to impact insurers, read our report: Technology Vision for Insurance 2021