In commercial real estate and insurance markets, the task of assessing risk and setting accurate premiums isn’t getting any easier. In 2023, a Swiss Re report revealed a striking gap: Only 40%, or $108 billion, of the $280 billion that was lost globally due to "natural catastrophes" was insured.

Much of this shortfall could stem from insurers having to gather critical property details—like construction type, usage, etc.—directly from property owners, many of whom simply don’t have precise answers. This can lead to significant protection gaps. That’s where point-of-interest data could come in. By providing deeper insights into property characteristics, market makeup and surrounding risks, insurers can use this data to refine underwriting accuracy, improve risk modeling and automate key processes.

But how can insurers actually use POI data? And how can insurers maximize their potential to navigate today’s risks while preparing for tomorrow’s challenges? Being the founder of a company that provides POI data, here’s what business leaders can do to stay ahead.

Getting Started With POI Data

At its core, insurers can use POI data to gain detailed, granular insights that inform underwriting, the process insurers use to evaluate risk and set appropriate coverage terms and pricing. Attributes like property type, business characteristics, industry composition and surrounding risk factors can provide a comprehensive view of a location’s risk profile. Understanding a business’s type, years in operation and the age and composition of neighboring establishments can help insurers conduct risk assessments tailored to specific market conditions.

What insurers can do:
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Begin gathering POI data. Insurers can consider options like using crowdsourcing information or conducting physical surveys to get started. But keep in mind that these methods can be resource-intensive and may not guarantee the accuracy, completeness and timeliness of the data. For these reasons, some insurers use POI data providers. If this is the route you choose, vet data providers thoroughly. Consider their data validation and whether they provide real-time updates. Ask about their sourcing and verification methods to ensure they're reliable.

Conduct regular data audits. Ensure your data is accurate and current by conducting periodic reviews of POI datasets, especially for critical markets and high-risk properties.

Integrate data into underwriting models. Supplement and refine existing risk models using your POI data. Focus on adding key property and neighborhood attributes to enhance precision.

This data-driven approach can help insurers assess nuanced risks and make decisions that more accurately reflect the reality on the ground.

Overcoming Data Challenges

The property and casualty insurance market is expected to grow by $757.5 million at a compound annual growth rate of 8.8% from 2023 to 2028, driven by advances in technology and changing consumer demands. To remain competitive in this market, insurers should prioritize data accuracy and learn how to use their POI data to help refine their risk assessments and automate decision-making processes. However, they'll also need to prepare for a few roadblocks.

What insurers can do:

Adopt data governance policies. Establish strict internal policies to maintain data hygiene, including standards for data accuracy, timeliness and relevance.

‍Address implementation challenges. One potential challenge insurers might encounter when adopting POI data is integrating it into existing systems and workflows. Incorporating it into complex insurance systems might require technical expertise. Additionally, insurers may need to invest in visualization tools to effectively leverage the spatial insights offered by POI data. Look for user-friendly visualization tools to help with this.

‍Layer POI data with other relevant data sources. This could include weather patterns, demographic information and historical claims data, and this process requires data cleaning, standardization and spatial analysis.

Moving From Reactive To Proactive Risk Management

Insurers can also use their POI data to shift from reactive to proactive risk management. Analyzing both real-time and historical data can help insurers detect emerging threats and provide early warnings to policyholders. For instance, by evaluating nearby construction sites, hazardous materials or demographic changes, insurers could alert clients to risks before they materialize and offer strategies to mitigate them.

‍What insurers can do:

Monitor industry-specific trends. Track changes in specific industries and geographic areas to anticipate emerging risks, such as increased climate-related vulnerabilities.

‍Adjust underwriting criteria. Develop underwriting guidelines that can be modified based on POI data insights. This can help ensure flexibility in response to evolving conditions.

‍Set up real-time alerts. Implement systems that monitor changes in POI data, such as new construction or changes in nearby business types, to alert underwriters and policyholders proactively.

‍Leverage historical data for trend analysis. Use historical data to predict potential future risks and tailor policy offerings accordingly.

Historical trends in industry behavior, economic indicators and local developments can provide insurers with a forward-looking lens. This capability allows them to anticipate future risks and tailor coverage accordingly.

Expanding Coverage To Underserved Markets

In my experience, traditional underwriting often overlooks emerging markets due to a lack of reliable data. However, insurers should consider how they can tap into underserved markets and offer tailored solutions in areas with limited traditional data, such as the Asia-Pacific region or South America. Attributes like business longevity, market composition and weather patterns can help insurers craft products that meet unique local needs and evaluate opportunities.

The high-net-worth market in the APAC region holds approximately 30% of global HNW financial wealth. This presents significant opportunities for insurers, particularly in property and life insurance, as growing household wealth leads to more valuable assets needing coverage.

‍What insurers can do:

Explore underserved regions. Analyze your POI data to assess market potential in what are traditionally considered data-scarce regions. Look for areas with specific demographic characteristics, economic activity and infrastructure development that align with your services. For instance, the presence of schools, hospitals and retail outlets can indicate a growing population and potential demand for insurance products.

‍Develop tailored products. Based on this data, create insurance products that align with the specific needs of these markets.

When used strategically, insurers can use resources like POI data to help navigate today’s complex risk environment, identify new opportunities, optimize operations and position themselves as leaders. Leveraging high-quality, reliable location data can help insurers remain agile, well-informed and prepared to tackle emerging challenges in a rapidly changing world.