Insurance data analytics: Three big steps to get started

In a world where people are beginning to find some insurance products redundant and irrelevant, it is vital for insurance companies to develop new products and strategies to stay ahead. Especially for today’s insurance business environment, insurance data analytics have never been more important.

Big data holds the key for agencies wanting to step into this field. It provides insurance companies insights they have not yet tapped into to enable them to expand into new markets and develop innovative products.

Best of all, it can be done quickly, easily, and with minimal risk. Many insurance companies spend a ton of money mining data, however, rarely exploit this data to its fullest potential in order to improve their company. Many companies end up sitting on invaluable data, which if mined and analyzed properly the start, would have given them insights to inform better business decisions. A sound Big Data strategy will help you avoid this scenario.

Many insurance companies, though they would love to launch a Big Data analytics initiative, find themselves struggling with where to start. We put together three simple steps for insurance professionals to start taking advantage of Big Data today.

1. Collect and group your data.

While the general idea of insurance data analytics may appear obvious, it does create some level of difficulty for first timers. The truth is, you will probably find it very hard to determine just what data you will need and what is irrelevant to your insurance needs. When you are just starting out you never know what you will eventually need, and for first timers, that means it is better to play it safe by retaining more data rather than discarding it.

Grouping data on the other hand refers to sifting through the data you already have and getting a rough idea of it while prioritizing it at the same time. You will probably not be able to get much business insight until you have an overview of just which data you have.

Remember also at this stage not to get rid of your current system! This will form a sort of foundation for your new data strategy. There’s no need trying to dig a new foundation when you already have one in place.

2. Develop a strategy for data governance.

This needs to be done early on while you are launching your insurance data analytics system to avoid the problems that can be caused by redundant data. Use business cases that have been substantiated using ROI metrics as guidelines to help you come up with your policiess on Big Data.

3. Do not try it alone.

Chances are your staff does not have the training they need to navigate your new Big Data strategy. Bring some experts on board to guide you through and help make the most out of Big Data for your insurance company.

The best Big Data software providers are those that have the skill and experience required, and more importantly, are willing to adjust to your company’s unique circumstances. These experts will help you create intuitive tools you can use in processing your data and enable you to do more such as testing hypotheses and answering questions you would not have been able to with traditional BI dashboards.

Stepping into Big Data analytics might be one of the best decisions any company can make. IKANOW is here to help you make these important steps as you set up your insurance data analytics system.

Learn More About Insurance Data Analytics

Gain an edge in the the growing field of data analytics with free Ebooks, whitepapers and other premium resources in the IKANOW Resource Center, or see how our open analytics platform can boost your business with a free one-on-one demonstration.

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