Bridging the US mortality protection gap

21 Sep 2018

Swiss Re Institute's latest Expertise Publication estimates that the aggregate mortality gap in the US, a measure of life underinsurance, was close to USD 25 trillion in 2016. In this report, we also forecast that the gap will widen in the coming years if current economic and insurance market trends continue. Insurance plays an important role in reducing peoples' exposures and we also look at the different avenues life insurers are exploring to help reduce the protection gap.

US mortality protection gap in USD trillions

Source: Swiss Re Institute

The gap is still wider than it was before the financial crisis of 2008-09
In Underinsurance in the US: bridging the USD 25 trillion mortality protection gap, we estimate that on a per household basis, the level of life underinsurance averaged USD 495 000 in 2016, equivalent to 45% of households' income replacement needs. There was significant widening of the mortality protection gap between 2007 and 2010, from almost USD 23 trillion to more than USD 27 trillion. The financial crisis of the intervening years resulted in a large increase in joblessness in the US, alongside a decrease in household asset values and an increase in household debt. These factors, combined with contraction in life insurance premiums, drove the gap wider.

Historical trends and drivers of the protection gap

Since 2010, the gap has narrowed alongside slow economic recovery, but it remains larger than in pre-financial crisis times. This is mainly on account of lackluster growth of the life sector overall and very slow increase in social security benefits relative to the income replacement needs. Between 2010 and 2016, life insurance coverage (measured in terms of premiums per capita) on average grew by 0.5% annually in real terms, and social security benefits by 0.2% annually. The combined contribution to the narrowing of the aggregate mortality protection gap was 1.5% annually, leaving the level of underinsurance still around 9% larger in 2016 than in 2007.

Macroeconomic projections point to a widening of the protection gap
We expect household income replacement needs to increase over the coming years given: (1) continued growth in incomes in the current cyclical economic upswing; (2) ongoing low growth of social security benefits; (3) a moderate increase in the value of households' financial assets; and (4) gradual recovery of the life insurance market to pre-crisis premium growth levels. We model a 0.8% increase in the mortality protection gap annually in the years to 2022. Further simulations reveal that life insurance coverage would need to grow by 1.5 percentage points more than our baseline forecast in order to stabilize the protection gap at 2016 levels.

Many people are interested in buying more insurance: why don't they?
Life insurance coverage has declined and remains below levels seen before the financial crisis of 2008-09. What's holding back the development of broader-reaching life cover? A first question to address is whether people are interested in buying life insurance. A recent LIMRA survey  found that among those who do not own life insurance, 39% recognize that they need it and 17% are not sure. This suggests that more than half of the people without insurance want or would be willing to buy cover if they can be convinced of the need for protection. And among those who do own life insurance, 19% say they do not have enough coverage and another 5% are unsure if their cover is adequate, another source of potential greater uptake.

The next question is why people do not buy life insurance, even if they recognize a gap in their income replacement needs. For 63% of respondents to the same LIMRA survey, insurance is deemed too expensive, 61% said they have other financial priorities, and 52% that they have sufficient cover. When asked how much the cost of insurance would be, most consumers estimated the cost at three times actual. Hence, a misperception of inflated costs appears to be another key reason for non-purchase.

Why don’t they buy more when they know they need it?

Sources: Swiss Re Institute; 2018 Insurance Barometer Study, LIMRA and Life Happens, 2018

Customer experience, behavioral economics and automated underwriting
Given the large impact of consumer perceptions on the buying process, life insurers are exploring three avenues to reduce the protection gap:

1) Using behavorial economics to gain a better understanding of the true drivers of customers' buying decisions. Studies have demonstrated the effectiveness of behavioral economics in improving sales and underwriting processes in accordance with consumer preference.

2) Accelerating the underwriting process to reduce the "frictional" costs of buying insurance. Insurers are also using technology to streamline the buying process by investing in more efficient tools which simplify and accelerate the underwriting process. Accelerated underwriting solutions reduce the average length of time from application to policy issuance by combining recent advances in predictive analytics and Big Data to avoid medical testing for some categories of clients. Such leveraging of technology and data analytics to evaluate client risk also makes it easier for consumers to buy life insurance.

3) Customer experience is emerging as another key priority area for insurers seeking to increase the perceived value of life insurance. The cost of buying life insurance includes more than money: it also requires information and time. Insurers offering customers better experiences that include a return on their information plus increased ease of doing business are more likely to achieve revenue growth.

However, within all three avenues of exploration, challenges remain. For example, insurers need to re-allocate resources to implement automated underwriting solutions and adapt their legacy systems. Another challenge is to expand outreach to more of the middle-income household population, which holds high growth potential. Here wider use of digital technology in distribution will play an important role.

For more, download the full report.

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