Filed Under:Carrier Innovations, Technology Solutions

Fully leveraging data analytics in insurance

Properly incorporating data analytics identifies customers' coverage options and helps carriers determine the likelihood that a customer will leave. (Photo: Shutterstock)
Properly incorporating data analytics identifies customers' coverage options and helps carriers determine the likelihood that a customer will leave. (Photo: Shutterstock)

This is the final of a series of four articles about the state of data in the insurance industry. Previously, we focused on the current state of insurance, customer demands and business models. While these topics are critical, to evolve the insurance industry, companies must also look at how they are using data for the betterment of the industry.

Insurance companies have significantly more data than some think. But the industry has been unwilling or unable to use the data to its fullest extent. However, by ignoring this data, companies are missing opportunities to better service customers and to improve business.

Acquiring data


Take a customer looking for home insurance. By simply entering a postal code and home address, this person can receive an instant quote online about the cost of the insurance. Now, from an insurer’s point of view, there is a ton of data that can be used to help this person: You can find internal and external data about weather risk, claims, construction, zoning, crime, accidents , and much other information.

These data points can provide patterns that can be used to help the customer get the right coverage while also protecting the insurance company from underwriting risk and fraud. The insurer can quickly marry this with the customer’s quote request to provide a very personalized quote. For example, instead of simply stating how much standard, minimum insurance would cost, your website could provide very tailored quotes.

This could include the standard insurance, but then you could put a short option at the bottom that includes the likelihood of an extra event, the average cost of a claim for that event and then the price for insurance that coverage. Between the small upsell and the improved customer service, it's a win-win.

Predicting the future


In addition to helping identify coverage options for customers, using data analytics can also help companies identify the likelihood that a customer will leave. It's common knowledge that acquiring a new customer is much more expensive than retaining a current one. If your database is up to date and clean, you can use algorithms around human behavior to start predicting which customers might leave. From there, you can specifically target them with tailored information designed to retain them.

The use of big data and data analytics is still an evolving practice but one that can seriously change the way that the insurance industry operates. If done correctly and with the right technology, updating data warehouses and applying data analytics your business processes can improve operations and you can provide customers with the customized service they crave.

This is the final article in a series from Jon Mayo of NIIT Technologies about how to utilize data in the insurance industry to decrease customer churn, increase revenues and lower cost. 

Related: Part 1, Losing clients: Ignoring these value-adds means customer turnover

Part 2, Is a hybrid distribution business model right for your organization?

Part 3, How to bring decades of data into the 21st century

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