Property & casualty insurance represents $1.6 trillion in premiums – about one-third of the insurance industry – according to industry reports, and the homeowners' insurance segment alone was worth $105.7 billion in 2020. As the industry continues to evolve, P&C insurance now benefits from risk models that analyze huge and diverse data sets. New data source influencers are emerging in the insurance industry, with the hope of providing the most comprehensive and accurate assessment of a property.
Many times, data is generated during the reinsurance process. One normal path for the data flow of a reinsurer begins with pricing. The goal is to analyze the risk and develop pricing estimates, so a complete understanding of the property risk exposure of a cedant portfolio is important for both reinsurers and primary carriers to adequately price and negotiate risk.
With property imagery, insurers now have a virtual way to closely view personal or commercial property and can easily validate property characteristics without leaving their desks. For customers, this makes doing business easier, as they no longer have to answer a seemingly endless list of questions.
For underwriters and agents, this means increased efficiency at point of sale. For instance, owners might optimistically overestimate the roof condition, or brokers might offer their best estimate for the total square footage. Advanced imagery-based data producers are making it more efficient to determine the condition and characteristics of a roof and accurately state square footage and many other features to allow underwriters to accurately price the risk.
Inspecting a roof is a time-consuming and potentially dangerous endeavor, so insurance adjusters are increasingly using imaging. When hail and wind events happen, image data can tell the insurance carrier which properties were impacted so they can deploy resources to the right areas and quickly estimate the cost of roof claims. In such instances, how quickly accurate data becomes affordably available post-event has a direct impact on the carrier’s bottom line.
Insurers are increasingly competing based on internal and external sources of data. Thus, it is also important for carriers to stay up to date on known attributes and strive to obtain new attributes as they become available. In general, these should be evaluated based on four dimensions.
1. Innovation: Are they persistently investing in research and development to add new attributes that were never available in the industry? For example, can they provide the height of a nearby tree and its distance from the property?
2. Confidence: How accurate are the attributes? Are they measured based on 2D or 3D images? Can they provide attributes like the number of floors and total volume? How accurate are they in stating square footage for a property?
3. Relevance: Can they make accurate damage assessment data available to the claims team post-event? How frequently can they provide updates to the property attributes? Also, can the claims team assess any roof damage in the form of missing shingles or presence of tarp on the roof based on the updates?
4. Cost effectiveness: Can they provide data for thousands of properties for a reasonable cost?
Personal and commercial property insurers are finding it increasingly important to use accurate, newly produced attributes for their property risks. They are rapidly making such data an essential part of their workflows and decision-making. The landscape of property claims and underwriting is becoming a lot more data driven and competitive, based on carriers’ ability to leverage newly available sources of accurate data. Only innovation-driven data producers that have advantages in multiple dimensions can create win-win scenarios for carriers.
Dr Upendra Belhe is president of Belhe Analytics Advisory, which helps businesses drive outcomes through data-driven insights. Guy Attar is co-founder and executive chairman of GEOX Innovations, a provider of property data for the insurance and real estate industries.
