Since the first accelerated underwriting programs came to market in 2012, these programs are increasingly viewed as the norm amongst life insurance carriers.¹ For purposes of this article, accelerated underwriting (AUW) is defined as the waiving of traditional underwriting requirements (e.g., fluids and medical exams) for a subset of applicants that meet favorable risk requirements in an otherwise fully underwritten (FUW) life insurance process.

Accelerated underwriting programs, despite being in existence for a full decade, continue to lack the mortality data needed to effectively monitor experience that we have grown accustomed to in traditional underwriting programs. Although the industry is getting closer, credible AUW mortality experience has yet to emerge due to the fact that the majority of programs came to market in 2017-2018. At that time, carriers piloted their programs with limited accelerated business, but they have slowly ramped up over the past few years. In addition, AUW-issued business is disproportionately made up of younger and more preferred risks compared to traditional underwriting, so most successful programs have seen few actual claims to date.

In the meantime, carriers rely on AUW monitoring practices as leading indicators of future mortality experience to inform their decision-making. These monitoring techniques can vary in their data sources, timing, prevalence, and selection approach (i.e., random vs targeted). The two most common forms of random AUW monitoring include:

• Random holdouts (RHO) - Cases in the AUW workflow that are randomly selected for additional underwriting evaluation, typically through the FUW process and before a final underwriting decision and/or offer is made.
• Post-issue audits (PIA) - Audits conducted after an AUW decision and/or offer is made, most commonly by reviewing an attending physician statement (APS) or electronic health record (EHR). The risk class determination from this evaluation is considered a proxy for FUW.

Both holdouts and post-issue audits can be conducted on a targeted selection basis, in addition to random. Targeted audits provide additional protective value by focusing the review process on cases with attributes that are associated with higher-risk policies (e.g., a problematic sales agent, a poor-performing distribution channel, policies flagged by MIB F or Rx Recheck). However, because targeted audits are skewed towards cases more likely to be misclassified, they are not as useful for mortality monitoring. For that reason, the remainder of this article will be focused on the two leading random monitoring methods: Holdouts and post-issue audits. 

Munich Re Life US monitors AUW programs using random audit data provided by life insurance carriers, which allows us to estimate future mortality experience based on underwriting risk misclassification within the AUW decisioning process. As of year-end 2023, we’ve collected 11 years’ worth of RHO and PIA monitoring data on over 33,000 lives across 30 AUW programs with the goal of capturing emerging mortality trends in the U.S. individual life accelerated underwriting market. For purposes of this analysis, we have excluded any AUW program dataset with fewer than 50 cases.

We use this data to derive mortality slippage, which we define as the implied mortality load relative to FUW mortality due to risk class misclassification in the AUW process. It is calculated on a present value of future claims basis using Munich Re’s internal view on a program’s mortality for a given age/gender/risk class. Risk class misclassification refers to differing risk class outcomes between the AUW and RHO or PIA estimated risk class.

This article highlights emerging accelerated underwriting monitoring trends and shares some of our high-level mortality slippage findings. 

There are several best practices that carriers can implement while monitoring their AUW programs, keeping in mind that estimated mortality slippage is only an indicator of future mortality experience and not based on actual claims experience. 

1. Start broad and scale down –  It takes time for a credible number of RHO or PIA cases to develop. Carriers that want to acquire learnings quickly will start with a high percentage of cases monitored, sometimes even 100% when they are in pilot phase. Once carriers are comfortable with the results, they can scale back to a more manageable monitoring level. Another reason for selecting more cases than intended to audit is to account for withdrawals in response to RHO selection, and not all cases requesting post-issue APS or EHRs will be returned.
2. Have a well-documented monitoring process and procedure in place – Monitoring data should be reviewed and evaluated by an experienced underwriter with the scrutiny as if the underwriter were evaluating the risk as new business. Target versus actual percentage of RHO and/or PIA cases, rescission thresholds, magnitude of rate differences, and source(s) and reason(s) for rate differences should all be noted. Also, if there is a rate class difference but rescission is not pursued, a file should be documented to prevent re-issue or reinstatement (without additional investigation).
3. Utilize available tools – While MIB Plan F and APSs are widely used, EHRs are emerging as a valuable PIA tool. Furthermore, prescription or medical claims histories can be utilized as stand-alone PIA tools or to triage APS or EHR reviews.
4. Be agile – Ongoing monitoring of programs can provide insight into pockets of business that may be experiencing higher misclassification and/or attracting anti-selection. Being able to react quickly to monitoring findings and adjusting program underwriting on the fly will allow you to close these loopholes before actual mortality experience begins to emerge.
5. Leverage your partners – Monitoring mortality slippage is a team effort. Engage your distribution and reinsurance partners in the process and sharing of results. Munich Re shares the results of our detailed carrier-specific monitoring analyses back with clients to share trends and high-level insights on their individual program. We can work with you to strengthen your AUW programs.

The lack of credible mortality data in still-evolving AUW programs means that carriers must continue to rely on AUW monitoring as an indicator of future mortality experience. Our study of AUW monitoring data found that an average program can expect to see mortality slippage in the 10%-15% range. While random holdouts generally result in lower overall mortality slippage compared to post-issue audits, using a combination of both monitoring methods could maximize AUW program learnings. Across both monitoring methods, most (81%) randomly audited cases are assessed at the same risk class as the AUW decision. Aggregate misclassification trends by policy level characteristics signal that males, older issue ages, and lower face amounts have higher mortality slippage. Tobacco misrepresentation remains a particular area of concern for AUW, and continuing to find solutions to combat this increasing misrep trend will likely continue to be a focus of the life insurance industry.

Munich Re has the expertise and experience with tools that can support carrier AUW programs. We have identified several AUW monitoring best practices, including starting with broad monitoring and scaling down as comfort grows, utilizing available tools, and developing agile procedures for quick reaction. As a follow-up to this paper, we’ll take a deeper dive into existing gaps in AUW programs and what can be done to close them.