Data raises questions, tracks performance, and helps companies reach their goals.
One of the least "sticky" products in the insurance industry is life insurance. Within the first three years 25% of policies lapse, and 40% lapse within ten years. The net result is that millions of people are underinsured, and insurers end up wondering where their clients went.
"The data raises questions," said Dror Katsav, CEO of Atidot, which provides analytics for life insurance. "The most immediate question that companies ask is, how good are they at evaluating risk and data?"
Katsav cites the example of an individual who has held a variety of employment positions, ranging from company founder to consultant. "The individual gets married, has a child, and is now settling down and looking for a house," said Katsav. "At this stage of his life, he becomes a better candidate for life insurance than he was before."
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Katsav said that insurance companies should look at information like this because "the biggest asset insurance companies have is data about customers and customer behavior."
New insights drive business
The goals of companies like Atidot is to discover these underlying customer behaviors and connect the dots so that insurers using analytics can see more than just the number of life insurance policies under management, or who has them.
"The object is to use your data to its fullest," Katsav said. "The greatest advantage is when you use that information to arrive at new insights that can drive your business."
SEE: Research: Big data and IOT - Benefits, drawbacks, usage trends (Tech Pro Research)
How do you get there?
Going beyond strictly transactional data will tell you how many policies and policy holders you have—and by aggregating this data with unstructured, big data such as the geographical locations of clients, what they do, their interests, recent life-changing events (such as a marriage or a child), etc. In this way you begin to understand more about the clients you sell to—or try to retain.
"Without big data in the equation you can't create the picture," said Katsav. "At the same time, you also have to change the culture of your company so that employees begin to use the data."
Digital transformation challenges
There are also challenges along the way as digital transformation unfolds.
"Digital transformation is happening so rapidly that business processes and employees are having a hard time keeping up," said Katsav. "With so many new kinds of data coming in, companies get overwhelmed. They are not sure which data to use for which purpose."
This is where an outside company that specializes in a very specific area, like, life insurance can help—but your success also depends upon what you do next.
SEE: IT leader's guide to achieving digital transformation (Tech Pro Research)
Here are four questions to ask yourself:
1. What is my business objective?
Life insurance is a one good example, because for years companies accepted lackluster results with life insurance. Consequently, they haven't really focused on it. If they are going to go after an underperforming product, they have to define an objective and commit the business to reaching it
2. If I need analytics, do I know how to aggregate the right kind of data?
If you want to learn more about your clients, you'll likely need to aggregate both transactional and non-transactional data to form a composite view of each client. To do this, you are likely going to require help. This is where it makes sense to bring in an outside expert.
3. Do I need to change my culture?
If your organization is wrestling with the impact of digital transformation and still adjusting to analytics, changes to culture and business processes might be needed. Cultural change is one of the most difficult challenges companies face. Allow time for it.
4. How will I know I reached my goal?
If your goal is to retain clients, to build your book of business or both—set realistic goals with a little bit of stretch, and track your performance after adding analytics.
- Big data policy (Tech Pro Research)
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- Research: Big data and IOT - Benefits, drawbacks, usage trends (Tech Pro Research)
- How powerful data analytics can be with the right tools (TechRepublic)
- Decision factors: Do you need real-time analytics? (TechRepublic)
- How vendors help companies arrive at meaningful business insights (TechRepublic)
- Insurance startup leaks sensitive customer health data (ZDNet)