3 Insurance Processes Where Digital Twins Can Bring Change

‘Digital twin’ technology is transforming organizations and industries worldwide, including the insurance providers. Digital twins are enabling insurance providers to predict newer and uncertain risks, settle claims faster, and enhance and accelerate their underwriting process.

Digital twins will soon become a disruption to the way insurance providers do business. It will soon replace the existing approach to risk and claims. Digital twins are a virtual simulation of real-life scenarios that can help teams to identify impact based on certain parameters. For example: Insurance provider for a shipping company can leverage digital twins to anticipate how a predicted storm can impact the ship and what can be done to minimize the risk or potential damage. This, in turn, allows the shipping company to take measurable steps such as calling the ship back or routing it through another channel to mitigate the storm. It enables the shipping company to minimize damage, and it helps the insurance provider to avoid a claim from the customer.

Impact of Digital Twins on Insurance Providers

Digital twins can rapidly shape the insurance sector and change the dynamics of their customer engagement, business operations, and revenue-making strategies. Digital twins enable them to also detect and predict new types of cyber risks that might rise in the future. Digital twins leverage low-cost cloud computing, faster data processing, and artificial intelligence for data extraction and image analysis. It gathers all the data to accurately develop digital models to predict risk of customer profiles without even having to visit them – such as manufacturing units, properties, freights, airplanes, etc. These digital replicas provide a platform for simulation where organisations can conduct ‘what-if’ scenario analysis and goal-seeking hypotheses testing.

Data Bridge Market Research analyses that the ‘digital twin financial services and insurance market’ was valued at USD 3.61 billion in 2021 and is expected to reach USD 12.07 billion by 2029, registering a CAGR of 16.30 percent.

Let’s look at 3 areas where insurers could take advantage of digital twins to gauge the risk landscape better and enhance their product offerings accordingly.

  1. Distribution

We have already witnessed insurance companies using data to understand the customer better and to cross sell other products and services wherever possible. However, digital twins take this approach one step further – by taking all data sets available about and around the customer such as their interests, travel, events, society, eating habits, fitness regime, etc. – and turn it into a simulated model where the provider can predict decision-making behaviour of the customer, its stimuli, and show relevant ads at relevant times when the customer has a higher chance of making a purchase.

  1. Claims Processing

Claims processing can leverage digital twins to improve its accuracy and process claims faster. For instance, in a car accident, the digital twin can help them simulate the conditions and predict the impact. The result can then be compared with the claim and processed accordingly. The technology will become smarter and more accurate with time and will bring the difference down between its predicted output and the claims raised.

  1. Intelligent real-time underwriting and monitoring

Digital twins’ main application in the commercial property line of business is to improve the accuracy of portfolio data, enabling insurers to carry out risk-weighted underwriting and ratemaking practices, reducing losses and creating for the first time the chance to offer risk prediction and prevention services by continuously monitoring risk exposure and external dynamics.

Digital twins are able to build real-life scenarios for insurance providers based on their insured customer profiles such as construction, logistics, manufacturing, retail, etc. These scenarios are then run with multiple parameters to predict the outcome and improve the underwriting. For instance, let’s imagine that a lot of home owners on the coast of Kerala are buying property insurance for their houses, and there is weather prediction of a catastrophic storm in the coming weeks. The insurance provider can leverage digital twins – feed in the weather data, geography, demographics, etc. – and predict the impact of such storm on the houses in that area. This will help them to price the risk, and underwrite these customers with the right premium.

Leave a Reply