Digital twins are virtual models of organisations’ assets and operations, connected to their real-world counterparts by back-and-forth flows of data. They can be anything from comprehensive models of integrated systems to simpler, more accessible tools to monitor a single asset. Businesses can use digital twins to optimise operations as well as risk management.
A real estate and facilities management businesses might use a digital twin to improve energy efficiency, which in turn can benefit sustainability risk management.
Virtual replicas can also help you test decisions before you make them, understanding how each move could impact the business ahead of time. This can reveal new efficiencies and strengthen resilience, helping you identify and mitigate risks more proactively and efficiently. Having a digital twin can also support better insurance outcomes.
As data storage and processing capabilities improve and relative costs reduce, digital twins are becoming accessible for more organisations. If you’re among those evaluating whether to introduce digital twins into your risk management and insurance approach, below, we summarise how your organisation might use and maximise virtual replicas. We also share some of the potential drawbacks and risk implications you’ll need to consider.
Businesses are using digital twins across a wide range of risk management areas, including preventing accidents and co-ordinating accident and emergency response. In the transport sector, we’re seeing digital twins being used to help prevent train derailments by simulating component damage and reacting to real-time data.
We’re also seeing organisations using digital twins to plan evacuation routes in areas at risk of natural hazards such as flooding and hurricanes.
More broadly, digital twins can pave the way towards more collaborative and data-driven ways of assessing risk, approaches capable of elevating your ability to manage risks. Engaging with your operations teams, for example, can give you access to real-time insights on system performance, letting you identify risks and vulnerabilities more efficiently and proactively.
You might also work with your sustainability team to create a digital twin to monitor waste and optimise energy use, helping to minimise sustainability-related risks.
Having dynamic, data-driven evidence of your organisation’s risk profile will also help you present your risks to insurers more persuasively. Demonstrating a mature level of data quality and overall risk management builds insurer confidence. This can make your risk more attractive to insurers and support better insurance outcomes.
Insurers are increasingly adopting their own digital twins to enhance how they assess risk and streamline underwriting. By creating virtual replicas of assets, infrastructure and even entire cities, insurers can simulate various risk scenarios, such as natural disasters, climate change impacts and infrastructure failures. In particular, some insurers are using digital twins to model the effects of extreme weather events, helping to refine policies and improve loss prevention strategies. Others are using digital twins to assess vulnerabilities in smart buildings and connected vehicles to evaluate the associated risks more accurately.
As the insurance industry and others continue to embrace technology, we expect digital twins to redefine risk management and insurance strategies, making policies more adaptive and data driven. We also expect AI-powered digital twins to enhance the precision of insurance coverage, as well as organisations’ resilience planning.
As well as offering a multitude of opportunities, digital twins can introduce new levels of cyber risk. As any effective digital twin contains large volumes of high-quality and real-time data, it’s inherently valuable to cyber criminals, especially if your system can make real-time adjustments to an asset or process.
Before introducing your digital twin, you’d be well-advised to get a deeper understanding of how it could alter your cyber risk exposure, the effectiveness of your current cybersecurity risk controls and the adequacy of your insurance.
Also, before introducing a digital twin, you’ll need to seek assurances on the quality, validity and consistency of your data. Your digital twin can only ever be as good as the data flowing in and out of it.
Finally, the complexities of modelling a changing physical environment in real-time demand on-going maintenance, regular recalibration and sophisticated validation to ensure your digital twin remains fit-for-purpose.
For specialist support to understand the risks and potential of technologies like digital twins for your organisation’s success and resilience, get in touch.
