The power of real-time risk data to transform commercial property insurance

By Anthony Peake, Founder and CEO, Intelligent AI

UK commercial property underwriting has made a loss for at least the last five years. According to Lloyd’s, the market has lost a combined £4.7bn against a total gross written premium of £50bn.

While there are many reasons for this, there is one significant underlying cause: commercial property insurers have not had access to accurate risk data in real time. This has led to inaccurate pricing or losing out on profitable risks due to an over-reliance on outdated information.

What’s more, insurers seem to recognise this fact. In a survey of 82 leading insurers and brokers, led by Intelligent AI, almost 90% of respondents said that real-time data was important to their business. Yet, only 38% said that they were good at accessing this data. Further, only a third of those surveyed (34.5%) said their organisation was able to deliver real-time data to their partners and customers.

Incomplete data leads to inaccurate pricing

Insurers urgently need to gain access to real-time data and move away from underwriting based on historic or incomplete data. Until they do, they are sadly doomed to continue pricing inaccurately. This is particularly true for risks that are influenced by climate change, where the value of historical data is largely void, due to the increased regularity and severity of loss events.

Another related example is where a property is located in an area that is susceptible to flooding, and insurers to assess the risk to be high just because it sits in a certain postcode, even if the property in question is a warehouse situated on top of a hill that just happens to be in that postcode. Real-time data will assess exactly where the property is, so that underwriters can make an accurate risk assessment.

Another example could be an office in an area with a high reported crime rate. An investigation might show that it is situated close to a police station, which inflates the crime figures for that area. The insurer prices the risk too high and loses the business, whereas the ability to see the building and understand why the crime figures are high would likely result in a more accurate and competitive quote by recognising the lower risk of being broken into or vandalised.

The reason for this inaccurate pricing is that too many insurers do not have access to live, accurate data, so instead have to rely on in-person, on-site visits. Yet, at the same time they lack the resources or budget to visit enough properties to get the data they need. In fact, our research shows that, on average, only 10% of insured commercial properties in the UK are visited by risk engineers. This means that insurers are underwriting an average of 90% of their property portfolio unseen. This is like buying a property without having a survey done first.

The opportunity is huge

Today, vast amounts of data exist to solve this problem. By gathering detailed location intelligence from open data, natural catastrophe data, satellite data, IoT data, and AI extraction of data from risk reports, insurers are now able to create real-time digital twins of the risks across 100% of their portfolios, not 10%, in order to identify risks and price them far more accurately.

All of this adds up to a huge global opportunity for the commercial property insurance sector to turn things around. But if this is the case – and insurers themselves recognise the opportunity – why has it not happened already?

For starters, it is no secret that the insurance industry is glacially slow to innovate, for many reasons. Also, insurers with loss-making commercial property portfolios have recently been more focused on increasing rates and tightening conditions in a hard market, over prioritising investment in technology.

This said, there is a lot to play for; in Intelligent AI’s survey, over 60% of insurers and brokers said they were ‘highly likely’, ‘likely’, or are ‘currently considering’ investing in real-time data and digital twins in the next 12 months as the economy grows and we return to a post-COVID normal.

The challenge remains implementation

What’s clear is the industry understands the need for change and how the lack of real-time data is negatively impacting operations. It also knows that real-time data could transform its fortunes, leading to more efficiency, more accuracy, and more profitable long-term client relationships.

Yet, accelerating the adoption of real-time data is not simple. Many insurers and brokers are saddled with legacy systems and siloed data, plus they have a lack of relevant skills. Respondents to the survey cited a ‘lack of senior management direction’, ‘lack of budget to invest in new technology’, and ‘the time it would take to see a return on investment’ as barriers to adoption.

Looking ahead, organisations that fail to overcome these barriers risk being left behind, underwriting poor risks at the wrong price, and making ever greater losses. Whereas, insurers willing to grasp the nettle and access real-time data via easy to access APIs will transform their fortunes.

The benefits for insurers that take action include more accurate risk pricing, lower cost reinsurance, 100% portfolio coverage, 360-degree view of risk, and lower claims and operating costs, meaning that commercial property insurance could become one of their most profitable books of business in the years ahead.

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