Underwriting: Top Technology Trends for Commercial Property Insurance in 2024

Despite macroeconomic headwinds shaped by rising risks, soaring costs, and business uncertainty, commercial property insurers continue to maintain earnings stability. But as the pace of innovation accelerates, small, habitational, and mid-market insurers will leverage technologies powered by AI, multimodal analytics that leverage high-resolution imagery and a wide array of other high-value data inputs to protect margins, reduce losses, expand share, and fend off increasingly sophisticated rivals. Here are trends our team ranks among the most relevant to commercial carriers this year. 

Real-Time Quote and Bind Becomes a P&C Imperative

In an era of rapid technological advancements and evolving risk landscapes, the necessity for real-time quote and bind in personal lines is undeniable. In 2024, momentum will extend to small commercial and habitational lines property insurance—a proposition that once seemed impossible but is quickly becoming low-hanging fruit. The challenge for many insurers will stem from traditional underwriting processes, which are time-consuming and data-poor.

AI-enabled technologies and high-quality data sources spanning an Internet of Everything are quickly rendering these processes obsolete. By leveraging modern property intelligence solutions, commercial lines carriers gain access to transparent, data-rich insights drawn from a multitude of trusted sources to understand and price risk quickly and accurately. 

Today’s most robust solutions provide precision risk assessment and loss-predictive property characteristics based on construction, occupancy, protection, and exposure (COPE) data, on-demand via API, batch, or web application to fit into automated or human-controlled workflows. For insurers, these technologies have been shown to reduce the time spent on an application by up to 80%, while providing risk-appropriate coverage and minimizing downstream exposure by catching ineligible properties at the time of submission. 

Commercial Lines Join the Embedded Revolution

When and where appropriate, these same technologies enable real-time, automated quote and bind to be embedded for the small commercial sector. Today, embedded insurance is coverage that’s bundled as a native feature with the purchase of third-party products or services that’s expected to generate $70 billion in revenues for US insurers by the end of 2025. 

It’s the Apple warranty for your iPhone, or the pet insurance offered with the purchase of a new dog collar. But increasingly, it’s also the auto coverage offered for that Ford F-150 work truck or that Cat EP16-2- Forklift—whether it’s one vehicle or a fleet of them. It can also be coverage sold to retailers, restaurants, and other commercial or habitational tenants through property owners or management firms. Or, coverage sold to organizations acquiring properties through builders, banks, lenders, and others. 

Today, technology providers such as Applied Systems, Modives and Bindable and others are bringing embedded commercial insurance solutions to P&C insurers. And according to Ernst & Young, embedded will increasingly appeal to commercial lines insurers that understand distribution is destiny—and that new business models enabled through partner ecosystems will be increasingly crucial to driving new revenue, better meet customer needs, and outmaneuver challengers and incumbents looking to do the same thing. 

Property ‘Info’ Without ‘Insight’ Proves a Costly Mistake

According to McKinsey, insurers employing modern data and analytics technologies can see loss ratios improve up to 5% through reduced claims, premiums rise as much as 15% by reducing underinsurance risk, and retention of their most profitable segments climb as much as 10%.

In 2024, a growing number of commercial property underwriters recognize that property intelligence analytics aren’t created equal—far from it. Many carriers will discover that AI-based commercial property intelligence is only as good as the scale and quality of the underlying dataset and the expertise of the human beings who train it. 

Anyone can source aerial imagery and a limited array of data sources to surface information within underwriter dashboards. And it would be fine if it actually delivered value. Instead, underwriters are left to sift through an impossible amount of data to draw conclusions on their own. The reason for this is because most providers hail from backgrounds in data science and computer vision. 

After extensive analysis and proof testing, our team formulated and refined a vastly different approach. It’s built around ingesting high-quality data from an enormous pool of public and novel sources, including high-resolution aerial imagery—and then applying geospatial analytics, computer vision, machine learning, and insurance-specific human expertise—to transform raw, often unstructured data into actionable, up-to-date insights, available on-demand. 

It’s also worth noting that this approach is also the first and only to correlate property attributes against the nation’s largest exposure and loss database provided by insurance carriers consisting of over 1 million property-specific exposure records and more than 700,000 location-level claims. In the year ahead, this kind of industry-specific, cross-reference corroboration will be of first concern for commercial carriers seeking the kind of precise and predictive understanding of risk that can spell the difference between gaining a better view on a property and one that enables an unrivaled edge. 

Roof Age, Complexity & Condition Intelligence Offers Unbeatable Accuracy

Roof condition data is a reliable proxy for the condition of the underlying structure. But commercial roofs tend to be much larger, more unique, and far more complex than residential roofs. There can be multiple levels, ventilation systems, and a host of other features that must be assessed. And unlike standard-issue asphalt shingles used in residential, commercial property roofing materials can range from built-up roofing systems to concrete to thermoset membranes and more. Leading commercial property insurers will recognize that getting an accurate view of risk and valuation requires roof information derived from models trained on complex commercial roofs.

Our Roof Condition Rating (RCR) for Commercial Lines solution underscores the importance of commercial-specific training data and is the only industry offering to do so. Here’s why that matters. Roof condition directly influences the risk level an insurer takes on when underwriting a property. An old, damaged, or poorly maintained roof can be a recipe for disaster when it comes to claims and payouts. And that can be consequential at a time when insurers face rising CAT losses, stubborn inflation levels, longer claims cycle times, and plummeting customer satisfaction. 

As a result, effective solutions must have the ability to leverage imagery, computer vision, and other forms of AI to analyze the number and types of structures on a property as well as roof geometry, square footage, materials, sizes, and more—both in the aggregate and for each individual structure. The ability to identify and analyze the makeup and condition of pitched shingle and tile roofs used in multifamily habitational buildings, or whether the roof of a particular structure in a corporate campus or manufacturing facility is made of corrugated galvanized steel, or flat, thermoplastic membrane, is critical to understanding risk. 

The latest version of our RCR product is able to assign risk scores based on the condition of each roof on a given property, and it’s specifically optimized to deliver accurate insights for these unique commercial roofs. In 2024, look for that age-old measure of roof condition—age—to be combined with property intelligence to offer insights that are far more predictive of loss than either of these two measures alone.

Look for carriers to prioritize solutions like ours, which incorporate reason codes, that have been shown to materially improve loss ratios by providing underwriters with objective information to clarify assessments. When assessing a single building, this kind of insight is valuable. When grappling with complex properties in habitational and multi-structure commercial, it becomes indispensable.  

Analytics, IoT Sensors & Satellites Power Innovation Against Climate Risk

Together with other technologies, the kinds of solutions we’ve discussed thus far will also prove critical to protecting against the growing impacts of climate change. During the 1980s, the US experienced an extreme weather event costing $1 billion or more every four months. Now they’re happening every three weeks, according to the US National Climate Assessment released in November. For full-year 2023, the price tag topped $100 billion in insured losses—for the fourth year in a row. 

Homeowners aren’t the only insureds getting walloped. As Moody’s Analytics points out, higher-value, higher-revenue commercial lines properties are often located in coastal areas with higher exposure to hurricanes. And the pace at which homeowners keep moving to wildland-urban interfaces (WUIs) vulnerable to wildfire is matched only by the speed at which businesses follow them there. Whether it’s a factory, retail mall, corporate campus, commercial farm, warehouse, or habitational complex, commercial properties in every corner of the nation face rising risk from disasters driven by atmospheric rivers, hail, wildfires, severe convective storms, and more. 

Adding exclusions and increasing premiums can only go so far. And the recent trend in pulling out of particularly vulnerable states will likely result in insurers ceding business to savvier competitors. In 2024, look for continued momentum in the use of solutions that allow commercial carriers to write business where less sophisticated insurers fear to tread—by pricing risk accurately and surgically avoiding bad bets. 

AI-based analytics solutions like ours, for instance, enable underwriters to quickly understand not just the unique exposure to specific risks for each structure on a commercial property, but also the extent and cost of likely damage. Others, like those from FloodFlash and ICEYE leverage radar-imaging satellites or IoT sensors to power new forms of parametric insurance to cover otherwise uninsurable properties and help close the protection gap for many climate risks.  

AI Doesn’t Replace Humans–It Empowers Them

Together, the rising expense and reduced availability of inspectors has been a factor propelling the need for intelligent, automated solutions. As it stands now, underwriters waste 40% of their day manually entering information on applicants, policyholders and properties—and scouring Google Maps. 

Take the lack of standardization in Statements of Value (SOVs). Submitted as part of an insurance application, SOVs can provide either a single address with a total count of buildings, or detailed information for each building within the property. Instead of what should be automated and instantaneous, a human is needed to map the available information in the SOV to a real-world property—a tedious process of matching each building on a property to an appropriate policy. 

Then there’s the task of translating and normalizing the wide range of formats and data received from agents and brokers in regard to COPE data. In the year ahead, look for insurers to embrace tools like Property Mapper, which enables underwriters to simply enter the address for an apartment complex or other multi-structure property and get an instant view of which building is associated with what policy—all automated directly into their workflow. 

Solutions like this give underwriters visibility into predictive property characteristics for accurate rating and underwriting—automating workflows where they can, and efficiently underwriting the rest with human supervision. 

A growing host of emerging complementary solutions have followed a similar philosophy. For example, NeuralMetrics offers real-time insights into an applicant company’s venture to close commercial coverage gaps and ensure that coverage remains accurate and up-to-date throughout the policy’s term. Meanwhile, Relativity6 offers API-based tools that predict the six-digit NAIC code for any business so commercial underwriters can confidently quote business, detect fraud, and provide more relevant marketing messages. And Carpe Data offers generative AI-based guidance for the commercial property underwriting process. 

In addition to automation, providing underwriters with the right information, at the right moment they need it, insurers can help agents, brokers, and insureds to implement risk mitigation measures and help shift from reactive, repair-and-replace operational models to proactive, predictive models as never before possible.

Commercial Property Intelligence Enters a New Era

With new sources of data, and the ability to apply it through AI, commercial property intelligence stands to become a significant differentiating source of insight and value for underwriters. What’s more, it can be leveraged to identify new opportunities, launch new products, and help make the business world more insurable. Carriers that fall behind are likely to find themselves at a significant disadvantage. 

To learn how commercial property intelligence can help underwriters select better risks, reduce expenses, and improve the customer experience, visit our commercial property intelligence page.