Why Granular Data Matters in Insurance

Mon Aug 10 2020

Most insurance companies were founded before the invention of color TV. That kind of tenure can be a double-edged sword: sure, the expertise is there, but what about a taste for change? The vision and desire to do things, well, better?

The truth is the home insurance industry at large is still stuck in the past. While waves of insurance innovation have come and gone, many insurers still have yet to adapt new data sources that allow for better pricing and underwriting.

That hurts you, the homeowner, because it results in coverage that may be overpriced yet doesn’t cover your true risk.

So we do things differently. We use new insurance data sources to help us provide more accurate and fair pricing. This lowers overall homeowners insurance costs and helps us serve coastal communities that need reliable, affordable insurance options.

Let’s take a look at how granular insurance data can make a big difference in your experience and the price of your coverage.

What Is Data Used For in Insurance?

To fully understand how new data makes insurance better, it helps to understand what insurers consider when evaluating your home for risk. Typically, your home insurance premium is based on a lot of factors, such as:

  • Your home’s location. Your location tells us a lot about your risk – like how likely your home is to experience a flood, wildfire, or robbery. It also tells us how easily you can access community resources that can help mitigate the severity of a loss (like your proximity to fire stations). Being able to understand details about a location and topography down to the individual block or property
  • Your home’s construction and characteristics. The age and construction of your home can tell us how well it will endure a big storm or other catastrophe. For example, homes with hip roofs usually better withstand hurricane winds than other roof shapes.
  • Weather patterns. The wind, rain, tides, and storm patterns in your area can impact your chances of loss.
  • Claims history. If you’ve experienced a loss that could have been preventable, it could impact your rates.
  • And more.

Granular data helps us get extremely precise insight into these variables instead of working with general data points (or outdated industry standards). The more data an insurance company has, the more accurately it can assess risk.

How the Old Way of Assessing Risk Increases Rates

Yes, all insurers use a lot of information to help price their policies. The problem is those rating models are then attributed to entire zip codes or even states.

That means even if your home has less risk, its baseline pricing is going to be the same as your neighbors.

This old model doesn’t necessarily factor in characteristics that make your home less risky. For example, say your home sits on top of a knoll in a flood zone. Your home’s elevation affects both homeowners and flood insurance. While you might get a percentage reduction from the baseline price, you are still paying fundamentally the same as your neighbors.

But when insurance companies embrace technology, everyone wins. Satellite imagery gives detailed information about the geography of your home. Thousands of data points give underwriters a better understanding of the real risk to your property. Using big data, insurance companies don’t just gather information – they compile it into useful details that algorithms run to accurately assess risk.

How Data Helps Underserved Regions

Florida has more than 2.9 million homes at significant risk of storm surge, which historically makes finding home insurance difficult and expensive. Same thing in California: 75 percent of the homes in wildfire zones are unable to get traditional fire insurance policies and have to get very limited and expensive FAIR Plan coverage.

Granular data helps us see the real risk each home has, and that enables us to insure more homeowners in catastrophe-exposed areas. We use satellite imagery and thousands of data points to gather information about each home and determine risk within the home’s neighborhood. So while Home A is still in the risk zone, it might have significantly decreased risk because of its surrounding topography.

By fairly assessing each property, we can manage risk better and offer lower rates.

Using Data to Reinvent the Customer Experience

When insurance uses big data, it creates a better customer experience all around. At Kin, we use granular data to help us quantify the frustration many folks have experienced with other insurers, from not being able to get insurance to sky-rocketing premiums to horrible claims experiences. In addition to helping us create new products, cut costs, and operate in regions most impacted by severe weather, we use data to:

  • Find out what is important to homeowners when it comes to insurance coverage and protection.
  • Tailor our marketing to your preferences.
  • Optimize your experience by resolving issues quickly.
  • Remove inefficiencies in both applying for insurance and processing claims.
  • Reduce company overhead and pass savings onto our customers.

Using data and technology to improve the customer experience doesn’t have to be earth shattering, either. Something as simple as drone mapping can help us find the most affected areas after a major storm, and using SMS to check in on customers – like we did after Hurricane Irma – can get the right resources to the right places and jumpstart claims sooner.

Getting new data sources in place means reimagining legacy systems and old ways of doing business, but it’s worth the effort. What’s more, our customers seem to agree.

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