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Life Health > Life Insurance

How big data helps the insurance industry

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Big data isn’t the future. It’s the present. And life re/insurers are making it a priority, using data-driven approaches to improve underwriting results and reduce the number of questions and invasive medical tests required in the application process.

All of this was inconceivable just a few years ago. Major factors driving this innovation are:

  • A desire to lead in technology and skills adoption;
  • Steadily increasing computing power;
  • Dedicated business analytics tied to data science algorithms, which are largely new to the industry.

These factors are putting the insurance industry at the forefront of sophisticated analytics on a scale that was previously out of reach.

In my line of work, I look at big data in two major streams.

In the first, big data is being used to help reduce costs and improve the efficiency of current processes throughout the insurance value chain, including claims and fraud management, cyber risk, customer management, pricing, risk assessment and selection, distribution and service management, product innovation, and research and development.

In the second stream, big data offers a new framework to think bigger in terms of market disruption. This has to do with innovation and how we believe new entrants could potentially disrupt traditional business models.

A key factor for rapid adoption of big data analytics is the direct link with connected devices that gather data and translate it into actionable information. Data streams can connect the consumer to the analytics platforms in real time as never before.

Most people have at the least a curious fascination with their health, and more and more are even developing a fanatical obsession with it. The Internet of Things satisfies our desire for health-related metrics and aids healthcare in its quest for decreased disease incidence—all of which aligns with our industry’s objective of reducing mortality risks. At the heart of this win-win-win scenario are big data analytics solutions powered by wearable devices. Examples are devices that help people with chronic diseases like diabetes live healthier lives and lead to improved treatments. Another highly anticipated outcome is the opportunity to expand insurance products to risk categories that were previously out of scope.

Yet this is only the start. In the future we see the insurance industry teaming up with public and private partners to push the digitalization of healthcare and biometrics through medical sensors and tele-healthcare solutions, with the ultimate goal of closing the protection gap between insured and uninsured population in the Americas.


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