Win Some, Lose Some in Accelerated Life Insurance Underwriting

Life insurance ownership has seen a decline in the recent past. There was an estimated $25 trillion gap between coverage purchased and needed in the event of a loved one’s death in 2016, in the US alone. Suboptimal processes might have contributed to this shortfall. Consider something as basic as getting a physical examination, often required to buy a policy. Research found that half of respondents were more likely to purchase if this invasive step was removed.

Life insurance underwriting has traditionally been a manual process. From collecting proof of insurability to assessing mortality risks of individuals, the application process can be overly tedious. In recent years, there has been a marked shift to accelerated underwriting (AUW), which waives underwriting requirements for select applicants. Most limit the scope of AUW to term life with face amounts between $100,000-$1 million and applicants in 18-60 age range. The pandemic sped up the adoption of AUW as the industry took to writing policies based on new technology, with less in-person contact.

On average, companies with acceleratated programs take 3 days (from application arrival) to reach the medical questionnaire – versus 8 days for traditional underwriting. For the final decision, the mean estimate is 9 days – versus 27 days for traditional underwriting.

While accelerated underwriting waives traditional requirements, automated underwriting automates underwriter activities. Most companies report that AUW programs have reduced policy issuance time.

Top (re)insurance companies have developed AUW platforms in which the underwriting manual is embedded as automated rules. Built on modern standards, these typically include workbenches to support workflow, APIs to incorporate third-party data and modules with cutting-edge AI (e.g. natural language processing). On some platforms, 90% of applications are processed within minutes, and a mere 5% percent require human touch.

Most accelerated pathways today are limited to simple products like term insurance policies. Fluid-less options are available only to relatively few customers who fit age and face-value requirements. In several cases, such limitations are aggravated by additional medical criteria with insurers choosing to accelerate only high-quality risks.. Consequently, many customers that start on an accelerated journey have to move back to a traditional manual underwriting path, leading to increased frustration.

One of the toughest challenges life insurers face when adopting AUW is determining how to compensate loss of information previously derived from tests. Insurance exams and fluid specimens reveal important evidence for risk assessment of life insurance applicants. Fluid-less underwriting gives up this value and carriers are exploring ways to offset the loss.

An example is Hannover Re that is collaborating with ExamOne, a Quest Diagnostics Company, to incorporate its LabPiQture data into Hannover Re’s AUW to enhance their automated capabilities and cut issuance time. ExamOne provides access to a comprehensive suite of real-time laboratory data – serum biochemistry, microbiology and toxicology – in a digitally standardized format.

The data and models used in AUW pose new risks for insurers. Assumptions about factors affecting mortality need further testing. Although medical data may be better correlated with mortality, behavioral data such as gym memberships, shopping habits, wearable technology and credit scores may lead to questionable conclusions. A high-income individual, perceived as someone with excellent medical care, may also have the resources for illegal drug use. On the contrary, a healthy young couple with lower disposable income to join a gym, may exercise on their own. The lack of a gym membership or lower income may not construe an increased mortality risk.

The approach of several companies’ accelerated or automated underwriting programs has been cautious, partly because insurers have taken an incremental approach to scaling automated decision making. These companies are opting for modest improvements to their risk frameworks and processes. With growing adoption and rising maturity, many more will look to embark on transformative programs.

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