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As the world becomes increasingly digitized, the insurance industry must take advantage of the rapid advances in the availability of IoT data, sophisticated analytics, and Generative AI. One technology in particular, digital twins, holds immense transformational promise.
Digital twins are virtual representations of physical assets, systems, and processes that are used to monitor and analyze performance in real time.
The digital twin concept is widely adopted in manufacturing and supply chain. I believe that digital twins will gain widespread adoption in the insurance industry within ten years. Insurers who take action to integrate this technology will significantly out-compete in the evolving insurance landscape.
The use of such real-time data and analysis is expected to help insurers create a more precise and more current understanding of risk. AI and machine learning models will be applied to these digital twins to produce highly accurate predictive and prescriptive analytics.
This is not some distant future vision. The insurance industry has long relied on data, with vast amounts of information being gathered throughout the rating, underwriting, and claims processes. Digital twins are now capable of leveraging that data in specific insurance applications.
Automobile telematics is a familiar example. Here, digital twins enable insurers to assess the risk of drivers and provide feedback to the drivers on how to improve performance.
Some may think that digital representations are inferior to their real-world counterparts. There are many examples to prove that this is not the case. Our industry has long used parametric securitization as an efficient and rapid access to post-catastrophe capital. In these structures, the real world insurance losses are secondary to the modeled parametric loss that actually triggers the bond payment.
Another example of digital twins is Swiss Re’s collaboration with Microsoft to establish its novel Digital Market Center that focuses on integrating connected vehicles, industrial manufacturing, and natural catastrophe data. While insurers can find immediate value in initiatives such as these, I believe that we are only beginning to scratch the surface.
In the near future, digital twins will be applied across the entire insurance life cycle providing real-time data and insights into customers’ insured assets – including data reported by IoT and smart sensors from their vehicles, property structures, and businesses.
For example, in underwriting, if we expand our definition of “inspection” to include digital twins, we can rapidly increase the inspection rate of commercial properties from 10% to 100%. While it may seem daunting to digitize so much of our world, Generative AI can be used to produce up to 85% of digital twin content.
In risk management, their application could look like Allianz’s use of ‘predictive maintenance’ for wind turbines. Predictive maintenance involves the use of cloud-connected smart sensors on the turbines being fed into analytical models and monitored by AI. By analyzing past performance and known characteristics, predictive maintenance aims to identify patterns and anticipate when maintenance should be performed, allowing for proactive maintenance to be carried out before a breakdown occurs.
More broadly applied, digital twins could be used to monitor and analyze real-time data from IoT sensors in insured assets such as homes or vehicles and identify potential risks or issues before they occur, allowing insurers to proactively mitigate them. It could also be applied in monitoring the cyber risk environment and informing an insured’s cybersecurity organization of new potential viruses, attack vectors, and risks.
The possibilities are endless. And the race begins in earnest now. I think it’s reasonable to expect that digital twins will come to dominate the insurance lifecycle by 2035.
How can you prepare and help drive your business towards this future?
For starters, embrace the idea of digital twins. Expect to see the insurance industry drive the adoption of IoT devices, connecting to 25% of all devices by 2035. So, incentivize IoT connectivity via new policies and renewals.
Recognize that virtual digital technology has the capability to manage physical environments. Digital twins will regularly intervene in the physical world to mitigate risks and drive preferred outcomes. So, build this expectation into planning.
One very promising application is that as digital twins become sufficiently realistic, this will increasingly allow for remote operation of dangerous machinery or in dangerous conditions, dramatically reducing accidents in industries like mining and oil extraction.
Understand that digital twin technology will complement insurers’ traditional role of indemnifying policyholders against losses. So prepare to use digital twins to more robustly assess and manage risks associated with insured assets, to monitor performance, and to take actions to mitigate those risks.
Guidewire will be there by your side for this journey. Just as we guided the industry to more robust and efficient core systems. Just as we are guiding many in their migration to the cloud. Just as we are helping industry innovators to embed analytics into daily workflows. So too, we plan to embrace the promise of creating a more digital and AI-centric world where digital twins are an ever-present technology.