In response to a flagging life insurance market, insurers have increased their investments in Simplified Issue Term Life (SITL) insurance policies to recapture market share among middle class consumers. SITL policies can be a boon by tapping into consumers who view life insurance as too expensive or wish to avoid visiting a medical professional before signing up for a plan.1
However, the low barrier to entry that makes SITL insurance so appealing to consumers also increases the risk exposure insurers face because they have less visibility into the health of the insured. Increasingly, insurers can mitigate this risk with predictive analytics by identifying the demographics expected to have a higher risk of filing a claim shortly after applying for an SITL policy. The implications of finding these high-risk consumers, either at the marketing or underwriting stages, could be huge as life insurers attempt to grow by reclaiming market share among middle-market consumers.
A changing industry
Life and annuities providers have faced a tough economic climate. Between 1985 and 2014, the life insurance industry returned less than its cost of equity with individual lines performing particularly poorly.2
The slow economic recovery from the 2008 market crash has resulted in a large amount of consumers not seeing life insurance as a priority primarily due to its cost or the availability of other investment vehicles like 401Ks. According to a 2015 report by LIMRA, 65% of Americans believe life insurance is too expensive; however, 70 million people said they needed more coverage.1 This number is key. If the industry could simply capture as many households in the $25,000 to $100,000 income bracket (estimated between 50 and more than 60 million Americans) as it held in 2004 alone, McKinsey predicts the industry would add $50 billion in revenue and $1 billion in profit. Younger consumers are particularly apt to overestimate the cost, but other insurers face challenges affecting the industry as well, including:
- Inaccurate cost expectations: Millennials overestimate the cost of life insurance by 213%, while Gen Xers overestimate the cost by 119%.3
- Preferred Methods of Contact: 70% of life and annuity customers prefer speaking to their agent or carrier via phone or email, rather than face-to-face.4
- Lack of Trust: 31% of consumers state they do not trust their insurance provider.4
Increasing opportunities, growing risks
More than a dozen insurers are offering policies without an exam, up from two in 2010.5 As these plans don’t require a face-to-face meeting, they effectively meet middle-market consumer demands for insurance to be available through phone or online methods of contact. This accessibility also helps insurers overcome misperceptions about the true cost of insurance. Once an agent is in contact with potential customers interested in a simplified issue product, they have to opportunity to educate consumers on the cost of fully underwritten plans, thereby creating opportunities for cross-selling or upselling.
These factors have led to a large amount of growth for SITL market share. One case study saw an insurer issue $87 million of these plans in 2015 up from just $34 million the year before.6
However the same characteristics (the lack of a medical evaluation and simple sign up) that make these plans attractive can expose insurers to a tremendous amount of risk. Although SITL policies typically require some kind of medical questionnaire, some applicants might omit conditions affecting their health or be unaware of them. To mitigate the risks SITL plans present, life insurers are able to increasingly leverage predictive analytics at both the underwriting stage and within the marketing process to bolster customer segmentation efforts.
Despite the risks of SITL programs and the advancements in predictive marketing analytics, most life insurers have yet to tap into these capabilities. In fact, less than half of life insurance companies employed a formal methodology to segment potential consumers into any meaningful subgroups and those who did used only basic demographic criteria, according to a study by industry association LIMRA.6 A one-sizefits-all approach to marketing simplified issue policies without segmentation powered by predictive analytics can result in significant losses among those most likely to file near-term claims, including high-risk groups that file within 18 months after the policy is issued.
Using predictive modeling to optimize opportunities
Insurers can use analytics to effectively segment prospective applicants in order to decrease the amount of loss exposure resulting from risky customer. By developing a predictive model based on a combination of financial and medical data, potential applicants at risk of filing a claim in the near future can be screened to not receive marketing materials. This can result in a significant reduction in loss exposure. According to two case studies, the top 5% of at-risk life insurance customers file approximately 39% of claims. This customer segment was found to be the only money-losing tranche for the insurer. By reducing just this segment of customers from a company’s marketing efforts, a significant amount of money was saved on paying out these avoidable claims.
The same predictive model used during the outbound marketing process could also simultaneously be applied to inbound leads. Prospective customers contacting insurers could be analyzed based on their medical and credit data to calculate their level of risk for filing a claim. Highrisk leads could be flagged as needing to undergo the full underwriting process. However, leads identified as possessing a low degree of risk could skip this process, saving insurance organizations a significant amount of time, effort and cost.
Over time, this predictive model could help insurers retain a large amount of healthy clients. The largest reason insurance customers switch providers is due to being offered a plan at a lower cost. However, if an insurer vets their leads and only accepts those with an acceptable amount of risk, the resulting savings could be factored into a lower pricing for their plans. Doing so would make the savings messages in competitor’s advertisements less effective, and allow insurers to maintain a healthy, low-risk book of customers willing to stay with their chosen carrier.