How Life Insurance Underwriting Is Changing

A crucial step in the process of placing a new life insurance policy is the underwriting procedure. However, this may also be the riskiest point in the sales timeline. A 2014 study from LIMRA found that as many as 18.7 million potential customers have given up in the course of underwriting and failed to ultimately commit to a policy.

“Underwriting is the most time-consuming portion of the life insurance sales process.”

According to insurance service PolicyGenius, underwriting is the most time-consuming part of the life insurance sales pipeline. It is also probably the most important, as it is the point when the carrier assesses the level of risk posed by a new policy and creates a fee structure that benefits everyone involved. Underwriting is essential for every kind of insurance policy, but it gets especially complicated in the case of life insurance. Factors like health history, age, gender and lifestyle are all critical components of an underwriting assessment, and some of these can take a significant amount of time to sort out. That’s why the underwriting process alone can take weeks or even months – no doubt a discouraging amount of time for many new policyholders.

If evaluating the risks of a new policy is actually the riskiest part of the life insurance sales process, approaching underwriting from a new angle should be a priority for forward-thinking insurance carriers. That’s the subject of a new study by LIMRA on the recent trend of automation in the life insurance underwriting process. In the course of their research, which involved surveying 61 life insurance companies, LIMRA found that many have already implemented extensive automation for their underwriting practices, with plans to work toward streamlining the process as much as possible. The goal of this automation is to improve operations from all angles, allowing insurers to better serve their clients in a timely manner, and hopefully leading to fewer abandoned sales.

How insurers automate

In their research, LIMRA noted that underwriting automation practices often fall into three categories: Fully automated, “triage” automation and partial automation. In their survey, it was found that two-thirds of respondents used at least one kind of underwriting automation, with triage being the favored approach. In this method, insurers will use a computer program that can sort through key details of each case quickly, sending uncomplicated cases through but flagging those that may require special attention. Of the 63 percent of insurers who used underwriting automation, just 30 percent were fully automated. Interestingly enough, 53 percent of automated carriers used a software program developed in-house, while 32 percent used a vendor-provided solution.

Life insuranceAdvanced automation algorithms and software could revolutionize the life insurance sales process.

The exact methods of automation and the sources for the information varied from each respondent but shared some common ground. LIMRA found that client-provided information about body dimensions, smoking, chronic diseases and driving history were basically universal in life insurers’ spectrum of underwriting research. The most used information source by far was the Medical Information Bureau. MIB was a primary source for 95 percent of respondents. Other common sources included prescription drug records, medical labs and motor vehicle records.

The many benefits of automation

Based on these findings, LIMRA concluded that life insurers who used more databases in their underwriting process witnessed the greatest benefit from automation and could reduce underwriting time significantly. They also note the rise of new technology that could make the research even faster, more accurate and more hands-off. Predictive analytics is proving to be a game-changer in many industries, including insurance. In 2015, Property Casualty 360 reported on predictive analytics technology’s rise and the huge difference it could make in claims processing. LIMRA expects similar disruption to come in the underwriting field. By gathering huge amounts of data together and analyzing it, predictive analytics technology has the potential to make underwriting faster and more accurate across the board. Although still in its infancy, data analytics is expected to become much more popular as techniques involving it become easier and more affordable for businesses.

Increased adoption and innovation in the realm of life insurance underwriting holds great promise in boosting revenue for companies involved. With greater rates of use and new developments emerging quickly, it’s not unlikely that the underwriting procedures of most insurance companies will look drastically different in a short amount of time.

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