Digital twins can empower insurers to overcome the climate crisis
Digital risk modeling is more precise than ever, fueled by weather intelligence, geography, demographics and more.
As natural disasters continue to sweep the globe, climate change brings increasingly unpredictable and damaging weather patterns that insurers must battle to ensure profitable yet competitive underwriting.
Throughout 2022 in the United States alone, there have been 15 weather-related climate disasters with losses exceeding $1 billion each. This is the eighth consecutive year in which the U.S. has endured ten or more billion-dollar disaster events, which have included drought, flooding, severe storms, tropical cyclone events, and wildfires. The National Oceanic and Atmospheric Administration estimates that damage costs from weather and climate disasters in 2022 could exceed $100 billion.
How can insurers stay one step ahead in this chaotic, destructive and temperamental risk landscape? They must use advanced technologies to undertake a risk management approach that encompasses inevitable yet turbulent hyper-scale events.
What are digital twins?
One way insurers can guarantee more accurate risk management by using digital twins, or virtual models that can accurately reflect a physical object such as a property.
Digital twins can act as a vacuum in which executives can predict and evaluate risk scenarios, taking cues from real-time updated data and virtually representing a problem so that a solution can be devised and tested in the program rather than in the real world. Digital twins achieve this through the utilization of low-cost cloud computing, faster data processing, and artificial intelligence for data extraction and image analysis.
Embraced by NASA in 2010 to create digital simulations of space and craft testing and named as one of the top strategic technology trends in 2017, the potential of the digital twins concept is now being fully realized in a multitude of sectors including insurance. Teams can identify impact based on certain parameters and create “what-if” scenarios and goal-seeking hypothesis testing to ascertain a valid and effective real world response.
An insurer’s new best friend?
Artificial intelligence (AI) is allowing insurance providers to automate the extraction of more rich and accurate data at an exceedingly rapid pace. Digital models are therefore more precise than ever, feeding from weather intelligence, geography, demographics, and more. Machine vision and deep learning can be used to automate fast, high-resolute extractions of 3D properties at scale. It is this type of data that digital twin platforms can harness to help insurers be more prepared for destructive and damaging weather events.
The main application of digital twins in the commercial property line of insurance is to improve the accuracy of portfolio data, allowing insurers to predict newer, uncertain risks by continuously monitoring risk exposure. Digital-twin technology therefore allows underwriters to gain a better understanding of risk pricing based on a multitude of scenarios including natural disasters such as earthquakes, floods and fires. The ability to test infrequent yet catastrophically damaging events means the underwriting process can be enhanced and accelerated. For the first time, insurers can offer risk prediction and prevention services and fix more competitive premiums.
Digital twins can help speed up claims processing through the technology’s ability to reproduce the event or circumstances surrounding the claim. The impact of damage to the client’s property can then be assessed and the insurance company’s liability determined.
The digital twins model also allows for the fast, reliable detection of fraud. By comparing the data from the virtual simulation of an event to the client’s real world case, claim adjusters can determine the claimant’s accuracy and detect inconsistencies that will ultimately reduce the carrier’s liability.
Several back-office insurance operations also can be improved using digital twins, ensuring transparency and avoiding any complicated legal disputes. Digital twins allow insurers to make critical business decisions by defining new policies and risk mitigation strategies. By enhancing core insurance operations through data gathering and digital asset simulations, companies can ultimately save themselves time and money.
The future of digital twins in insurance
Where insurers previously relied on historical data sources to assess financial risk, modern analytics tools such as real-time data analysis have transformed the industry. Nearly nine out of ten insurance executives agree that digital twins would strengthen their ability to collaborate in strategic partnership ecosystems, which are crucial for long-term success. One company that is already one step ahead of the trend is the reinsurer Swiss RE. Their partnership with Microsoft has allowed the carrier to build a digital twins virtual world that utilizes AI and real-time data to simulate and analyze risk scenarios. This foreshadowing of disasters, both natural and financial, allows the insurer to undertake cost-effective interventions.
In the face of erratic and damaging weather patterns and an increasing unstable climate environment, digital replicas and up-to-date, accurate computational models such as digital twins can help insurers price premiums, assess the market, accurately and efficiently process claims, organize back-office administration, and quickly and reliably detect fraud.
Digital-twin modeling is rapidly changing the way the insurance sector engages with customers. It is altering the dynamics of business operations to ultimately set more competitive premiums and settle claims faster. Insurance is now prepared to transcend into the new era of assurance.
Izik Lavy is the CEO of GeoX. These opinions are the author’s own.
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