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    Home»Big Data»5 Use Cases for Enriched Data in the Insurance Industry
    Big Data

    5 Use Cases for Enriched Data in the Insurance Industry

    AdminBy AdminNovember 27, 2025No Comments6 Mins Read0 Views
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    5 Use Cases for Enriched Data in the Insurance Industry
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    At its core, the insurance industry is about accurately predicting risk, pricing policies to cover that risk, and minimizing fraud. Enriched data, like geospatial data, adds critical context to existing information about policyholders, insured properties, and more.

    For data-driven insurance companies, data about properties, locations, and their physical characteristics provide a competitive advantage.

    Now, insurers can take this even further with solutions like Precisely Data Link for Dun & Bradstreet, which pre-links business and location data for a complete, unified view of risk. With unified data that combines occupancy, property, and climate risk insights with payment, ownership, financial strength insights, you can improve underwriting precision, speed up decisions, and reveal hidden exposures across your book of business.

    For data-driven insurers, enriched data provides greater accuracy, speed, and confidence across the policy lifecycle. Here are five powerful ways enriched data can improve profitability and performance in the insurance industry.

    1. Improve underwriting and pricing decisions

    For years, insurers have treated location as a coarse-grained data point – relying on information like city, town, or zip code to assess risk. But when every insurance company in the market is using that same approach, it becomes more of a “good enough” baseline rather than a competitive advantage.

    Today, insurers have access to far more detailed location context to make smarter, more informed underwriting decisions.

    Take, for example, two policyholders who live on the same street: Chicago’s Western Avenue, which is about 24 miles long.

    • One home is near a dangerous intersection in a very congested area. It has a high crime rate and is near a series of abandoned buildings.
    • The other home is in a reduced speed area, close to a school and high-end stores, with a lower crime rate.

    Should those two policies be priced the same? To easily identify these differences and price accordingly, enriched data with location context is key. And with Data Link for Dun & Bradstreet, you can go even further – accessing pre-linked business and location data that eliminates the need to manually connect disparate datasets. That means faster, more accurate underwriting decisions, plus visibility into businesses and co-tenants that may influence property exposure.

    Read the Forbes Insights report

    Pinpointing the Issue: Why Hyper-Accurate Location Data Can’t Be Overlooked in Insurance

    If you are an insurance professional interested in exploring data enrichment as a path to increased competitiveness, we invite you to download this Forbes Insights report

    Read

    2. Telematics and the Internet of Things (IoT)

    Commercial fleets are equipped with telematics devices that track location, measure driver performance, and assess the operational health of the vehicle. These same technologies are also making their way into the consumer market as well – especially as smartphones make it easier to collect and share information about a policyholder’s location and driving habits.

    Some insurers now offer usage-based pricing programs that track mileage, location, and driver behavior through mobile apps. While privacy remains a concern for some, many policyholders welcome the opportunity to save money in exchange for sharing their data.

    In healthcare, wearable sensors and at-home diagnostic devices can provide insights into physical activity, vital signs, and alerts to potential emergency situations.

    Just like in telematics, many people will opt out of sharing such information – but insurers that can securely incentivize this data sharing open the door to mutually beneficial relationships. Policyholders who do share that information may receive discounts or other benefits in exchange for valuable real-time data.

    3. Risk mitigation

    Major weather events account for billions of dollars in claims every year. By analyzing historical weather patterns and the damage they cause, insurers can predict the likely impact of future events like tornadoes, floods, and hailstorms with a high degree of accuracy.

    5 Use Cases for Enriched Data in the Insurance Industry

    When insurers understand where damage is most likely to happen, they can warn customers in advance to help prevent losses before they occur – encouraging them to move cars into garages before a hailstorm, for example. They can also pre-position claims adjusters in the areas that require closer attention and on-the-ground assessment.

    When combined with Data Link for Dun & Bradstreet, insurers gain an even clearer view of exposure – linking weather data with property and business insights to understand not only where damage might occur, but which policyholders and nearby businesses are most at risk.

    4. Fraud detection

    With detailed information about risk scenarios and location-based impacts, insurers can identify fraudulent claims faster and with greater accuracy. For instance, if predictive models tell us that a particular area suffered little or no damage, then catastrophic claims from that area can be flagged for closer review.

    Access to integrated business, property, and risk data through solutions like Data Link for Dun & Bradstreet helps insurers validate claims more efficiently and pinpoint inconsistencies that could signal fraud.

    Enriched data image 2 File folder with tags.

    5. Improve marketing spend

    Customer databases have long been plagued with inconsistencies, inaccuracies, and duplicate records. In the simplest scenarios, that means money wasted on duplicate mailings and other customer outreach efforts. But the impact goes beyond that.

    Data enrichment adds valuable context – helping insurers understand relationships across their customer base. For instance, a personal auto policyholder may also own a small business and need commercial coverage. Traditional databases rarely make that connection, but enriched, linked data can.

    Data Link for Dun & Bradstreet enhances this visibility by connecting business occupancy, property, and location data in one view. That means insurers can uncover relationships between policyholders, identify potential cross-sell opportunities, and engage customers with more relevant offers at the right time.

    Data enrichment also brings context to customer information in the form of major life events like graduations, job changes, home purchases, new children in the family, and more. Each of those events implies some major shifts in a person’s needs for insurance and other financial services.

    The Power of Pre-Linked Data

    While differentiated services or products may help you win customers, it’s an insurer’s ability to accurately assess risk and price its premiums that drives long-term profitability. Enriched data – and now, pre-linked business and location data from Data Link for Dun & Bradstreet – makes that possible.

    By strengthening underwriting, enhancing exposure management, and improving decision speed, Data Link helps you build a foundation of trust in your data and pricing models.

    If you’re an insurance professional looking to boost competitiveness, be sure to check out our insurance datasets. And, read this Forbes Insights report: Why Hyper-Accurate Location Data Can’t Be Overlooked in Insurance.

    The post 5 Use Cases for Enriched Data in the Insurance Industry appeared first on Precisely.



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