Digital twins: How to obtain a 360-degree view of property risks 

As property risks become more complex and interconnected due to pandemics, natural catastrophes, economic hardship and other challenges, insurers need to dig deeper and harness more meaningful and diverse data for better risk analysis. According to Anthony Peake, whose company Intelligent AI focuses on precise risk modelling, the commercial property market needs modernising and stands to benefit hugely from the insights provided by richer and more actionable data.

The commercial property challenge

“Insurers and brokers lack the comprehensive real-time risk data they need to monitor, detect and mitigate commercial property risks,” says Peake. “Only 5-10 percent of commercial property locations are physically inspected for risk and, even in those that are, less than 25 percent of risk recommendations are followed up.”

Peake adds that commercial property insurance is running at a loss, emphasising the need for a new approach and better risk intelligence. According to research by Intelligent AI, almost 90 percent of insurers and brokers who took part in its 2021 survey said they struggled to gather good levels of data on commercial property portfolios. What’s missing are location-based insights using a wide range of data points backed by artificial intelligence.

This is where the power of digital twins comes in. “A digital twin can provide a 360-degree view of risk across 100 percent of your portfolio,” says Peake. “It will drive smarter underwriting and a stronger risk management approach, and it represents a shift from reactive to preventative insurance.”

Peake explains that Intelligent AI can build digital twins from hundreds of data sets. They include open data (such as crime, fire, rateable value or financial data), satellite spectral analysis data, internet of things (IoT) sensor data, real-time catastrophe data (such as watercourse, flood, temperature, weather and seismic data), and AI-generated and AI-extracted risk report data.

Risk identification and mitigation

”With digital twins, you can digitalise an entire commercial property portfolio,“ says Peake, “and analyse risks across all locations. You have total oversight and can scale as required. Dashboards provide a view of risk at any single location, or on a client or portfolio level, and provide benchmarking. Analytics, artificial intelligence and predictive modelling are then used to calculate risk scores and identify opportunities for risk mitigation.”

Peake says that being overly reliant on historical data leaves insurers exposed, as it provides only a partial view of risk, while real-time actionable data derived from digital twins and AI can promote accurate risk selection and pricing, and help prevent catastrophes.

“Losses and unexpected exposure are inevitable with traditional methods,” says Peake, “because a huge proportion of insured properties are not visited, and the statistical models used to predict risks in unseen locations can be unreliable. Digital twins are proving to be far more accurate than statistical models when predicting risk across the vast majority of properties not seen by risk engineers.”

Peake says that if you have a digital twin, AI can carry out desk surveys at a fraction of the cost, enabling insurers to quickly identify high-risk versus low-risk properties. Portfolios can be steered to encourage a diverse mix and balance risks, and with a better overview of their portfolios, insurers can develop risk improvement programmes.

“Poor visibility of risk is not sustainable in today’s climate,” says Peake. “With global location intelligence and predictive algorithms, insurance becomes more about partnership than policies. Risk analysis and loss prevention are critical, and with the right data points and modelling, insurers can improve protection and bring down costs.”