Property data influences nearly every part of the insurance process. For public entities that are managing large property schedules, the quality of that data can affect valuations, underwriting, renewals, and claims, potentially affecting the entire organization.
For many public entities, their processes involve a combination of manual effort, limited time, and limited resources to evaluate property data as a whole and improve accuracy and efficiency. At the same time, underwriting has become more detailed, and expectations around data accuracy and completeness have increased. Together, this puts pressure on public entities to bring more to the insurer’s table to get the coverage they need and reexamine their processes for collecting and maintaining that data.
This article will discuss why insurer data goals have shifted, what quality data looks like today, and how organizations can modernize their property programs, bridging the data gaps to ensure better coverage and better rates.
Why Data is Getting More Attention
Today’s insurance carriers are working through a combination of challenges. With an aging U.S. infrastructure and an increase in catastrophic weather conditions across the nation, insurers continue to see high claim volume and severity. Moody’s reports that global catastrophes in 2025 caused approximately $224 billion in economic losses, with estimated insured losses around $108 billion. Over 80% of that total was from catastrophes in the United States, including severe convective storms and the California wildfires in the first half of 2025.
In reaction to these catastrophic losses and more localized risks, underwriting teams are relying more heavily on detailed, property-level data to gain a more thorough view of an organization’s risk level.
When that data is incomplete or inconsistent, it often leads to worst-case scenario assumptions on the part of insurers, which can lead to lower carrier confidence, reduced ratings, and higher premiums. In harder markets, it can even lead to a loss of continued coverage, where retaining insurance becomes more competitive, and insurers gravitate toward insureds with lower risk profiles.
Where Today’s Data Challenges Pop Up
It’s typically a lifetime of lingering data maintenance and storage processes that continue to cause modern property insurance data challenges. Many organizations are still managing property data across multiple spreadsheets, controlled by different staff and departments, and tucked away in siloed software systems. This causes version control issues. Data has to be extracted from different systems and compiled, often by hand. It can make it hard to pinpoint missing or outdated property attributes or inconsistencies. And it becomes challenging to highlight and assess conflicting valuations on similar property types across an entire risk pool.
To complicate things further, these issues tend to surface during renewal time, when carriers request more detailed information. With data in so many disparate locations, the process to rectify everything is often highly manual, while staff members are under a time crunch. It becomes hard to take the time to seek out and analyze red flag data or catch the other small details that could lead to big omissions in your overall Statement of Values. Underwriters need a clearer picture of your exposure for specific properties.
What Modern Property Data Looks Like in Practice
Today’s insurers want to see more standardized property data, greater submission transparency, and the analytics behind valuations, to help increase confidence in their underwriting decisions.
Thorough property data includes (but is not limited to):
- Consistent data structure across all properties
- Complete COPE data and valuation inputs
- Accurate coordinates, square footage, and ISO classification information
- Distance to fire hydrants and fire stations, as well as interior fire safety technology
- Pertinent wind or flood zone information, and the architectural features that are more commonly affected by wind or flood
- Any catastrophe or convective storm modeling (if applicable)
Your insurer can provide you with a list of data points they require, so you can make the most of your organization’s data-gathering process. Make sure you choose a qualified property valuation partner and share those requirements with them to get the information you need during any appraisal projects. But organizations that maintain accurate data, understand their highest-risk properties, and take a structured approach to mitigation will be better positioned as conditions continue to evolve.
Steps to Modernize Your Property Data Strategy
The good news is that modernizing your property data (aligning with what insurers look for when you go to market) can start with a few practical changes:
Centralize Your Property Data: Move away from disconnected spreadsheets by centralizing your property data in risk management software, with individual user access for stakeholders, no matter their location. This helps reduce data duplication and version control issues. It also helps save time; it speeds up information-gathering during the renewal process, when time is at a premium. It helps maintain consistency across risk pools and municipalities. It increases accountability, allowing you to track which changes were made and by whom. It creates a history of each property and its updates. And its search and reporting can help you uncover outliers and other inconsistent data across the system. If the system has policy capabilities, it can even help speed up a risk pool’s renewal process, taking it from tiring manual efforts to cleaner, more automated ones. (Learn about our RiskStar policy module here.)
Configure and Standardize Key Fields: Establish consistent definitions for construction type, occupancy, square footage, and more. An effective risk management system should let you configure the fields so they’re labeled with the familiar terms your organization uses. This helps your team adopt the software more rapidly.
Audit Data Regularly: Routine reviews help identify data gaps, outdated values, and inconsistencies before they affect underwriting. By taking advantage of the quieter times outside of renewal season, you give yourself the opportunity to truly analyze and strengthen your data.
Showcase Clean Data in Easy-to-Present Reporting, When You Go to Market: When you arrive with clear, easy-to-understand values with the accurate data to back them up, you increase insurer confidence. This can help shift a low rating to a more affordable one. And when you manage public municipal funds, good stewardship can make a big difference to your community!
Seek out valuation expertise: It’s important to value your property every three to five years. But it’s equally important to make sure you have a valuation partner that captures all the data points you need. Additionally, if you have unique structures such as water or wastewater treatment plants, you need a valuation team that understands the nuances of appraising them, too. When it comes to property data, the details matter!
The Bottom Line on Property Insurance Data
Accurate property data supports more than insurance placement. It can also help support:
- Capital planning
- Maintenance prioritization
- Long-term risk strategies
- Initiatives for proper stewardship of public funds
The benefits are significant, but it’s important to remember that improving property data isn’t a one-time-and-done process; it’s an ongoing process. By unifying and maintaining your property data year-round, with frequent audits and trusted valuation every three to five years, you can come prepared with the data that wows insurers at renewal time.
Note about this article:
This article was drafted by AI, and human-edited by our team.