This is the first blog in a series on Predictive Modeling in Life Insurance

Today, the life insurance industry is facing challenges like never before. Yet, consumers’ need for protection remains. So, for insurers, the issue is how to overcome these challenges. One such issue they face is how to manage the expectations of today’s connected consumer.

It’s all About Speed

Consumers are no longer empowered, they are emboldened. Technological advances have given them faster and easier access to information, other people, and products and services. This has resulted in the widespread expectation that speed and convenience should be inherent in all transactions. The purchase of life insurance is no exception.

In fact, the 2017 Individual Life Insurance Consumer Survey1 shows an increasing interest among consumers of all ages for speed, ease and transparency in the life insurance purchasing process—with having a product that is “easy to understand” ranked a top priority (83%) for those considering the purchase of life insurance.

This development clashes with the traditional underwriting process, in which proposed insureds must often complete invasive medical requirements in order to obtain coverage in what they view as a drawn-out, time-consuming process.

Research underscores the need for change: According to the 2017 Insurance Barometer Study2, 70% of Americans who would consider purchasing life insurance would be interested in doing so without a physical exam (through what is also known as simplified issue).

The Need for Protection is Real

Findings from the 2017 Individual Life Insurance Consumer Survey revealed that 1 in 4 American households recognized the need for life insurance in the 24-month period before the survey. This suggests that 31 million U.S. households entered the life insurance purchase process. Yet only 7 percent of those households actually purchased coverage.

One Solution: Real-Time Data & Analytics

With respect to the time it takes to underwrite a policy, a large portion of the process is devoted to data gathering. But this is where technology can actually help insurers. Thanks to real-time data and advanced analytics, elements of the underwriting process can now be effectively automated. This enables routine risks to be fast-tracked through the underwriting process—freeing underwriters to focus on the complex risks that deserve closer evaluation.

Insurers can now leverage vast amounts of data—aka “Big Data”—and the ability to use analytics to derive insights from it. It can all be done quickly and easily. In fact, Big Data is changing the game in the life insurance industry by helping life carriers:

  • improve the customer experience;
  • work smarter (not harder); and
  • attract new business.

Real-Time Data & Analytics in Action

Our predictive modeling solution, LexisNexis® Risk Classifier, provides life insurers with a numeric score that corresponds to a proposed insured’s risk profile. Using Risk Classifier enables underwriters to make more consistent, informed decisions. And carriers can optimize underwriting spend and price policies more competitively—which can allow insurers to offer their customers faster, more convenient service.

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1 Source: The Purchase Funnel — Tracking Consumers Through the Life Insurance Purchase Process, LIMRA, 2017

2 Source: 2017 Insurance Barometer Study, LIMRA and Life Happens.