The New Normal for Advanced Risk Selection
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Introduction
Munich Re Life US conducted its third accelerated underwriting (AUW) survey in late 2022 with the aim of capturing new and emerging trends in the U.S. individual life accelerated underwriting market. The primary goal of the survey was to compare current results to prior surveys in 2018 and 2020 to highlight key developments over the past several years. The secondary goal was to further explore the growing use of underwriting tools, particularly digital health data, in accelerated underwriting programs.
For purposes of the survey and this paper, AUW is defined as the waiving of traditional underwriting requirements (e.g., fluids, medical exams) for a subset of applicants that meet favorable risk requirements in an otherwise fully-underwritten life insurance process. This article highlights emerging accelerated underwriting trends and shares some of our high-level survey findings.
Survey Highlights
- Accelerated underwriting is now a full decade old with the earliest programs having been brought to market in 2012.
- AUW face amounts, which rapidly increased during the onset of COVID-19 in order to meet the demand for socially distant underwriting options, remained in place and even continued to grow, post-pandemic.
- Eligibility, acceleration, and offer rates also increased. However, a large proportion of AUW decisions still have some level of human involvement.
- AUW programs with higher acceleration rates share several common characteristics, with examples including multiple distribution channels and variety of underwriting tools used.
- Testing and adoption of digital health data sources, such as medical claims data and electronic health records (EHRs), is growing among carriers.
AUW Trends over Time
The 2022 AUW survey represents results from 31 companies, all with an AUW program in production as of June 2022. Earlier surveys had a similar number of participants, with slight differences in the mix of carriers represented.
Eligibility Parameters
Figure 1: AUW Eligibility Trends Over Time
![Figure 1: AUW Eligibility Trends Over Time AUW Eligibility Trends Over Time](/content/dam/munichre/marc/images/2022%20AUW%20Survery%20-%20Figure%201%20-%20AUW%20Eligibility%20Trends%20Over%20Time.png/_jcr_content/renditions/original./2022%20AUW%20Survery%20-%20Figure%201%20-%20AUW%20Eligibility%20Trends%20Over%20Time.png)
While there has been a noticeable shift in maximum face amount offerings in recent years, it is important to keep in mind that not all AUW face amounts are available to all AUW-eligible issue ages. The number of AUW programs offering a banded age and amount eligibility structure continues to grow, with now nearly half of AUW programs limiting their maximum face amount offering to younger age bands.
Product Availability
While we saw a notable jump in AUW programs introducing permanent products between 2018 and 2020, this appears to have leveled out in 2022, as detailed in Figure 2 below.
Figure 2: Product Types Offered Through AUW Programs Over Time
![Figure 2: Product Types Offered Through AUW Programs Over Time Figure 2: Product Types Offered Through AUW Programs Over Time](/content/dam/munichre/marc/images/2022%20AUW%20Survery%20-%20Figure%202%20-%20Product%20Types%20Offered%20Through%20AUW%20Programs%20Over%20Time.png/_jcr_content/renditions/original./2022%20AUW%20Survery%20-%20Figure%202%20-%20Product%20Types%20Offered%20Through%20AUW%20Programs%20Over%20Time.png)
Risk Class Structure
Figure 3: AUW Risk Class Availability Trends
![Figure 3: AUW Risk Class Availability Trends Figure 3: AUW Risk Class Availability Trends](/content/dam/munichre/marc/images/2022%20AUW%20Survery%20-%20Figure%203%20-%20AUW%20Risk%20Class%20Availability%20Trends.png/_jcr_content/renditions/original./2022%20AUW%20Survery%20-%20Figure%203%20-%20AUW%20Risk%20Class%20Availability%20Trends.png)
Key Metrics
Table 1: Eligibility, Acceleration and Offer Rate
![Table 1: Eligibility, Acceleration and Offer Rate Table 1: Eligibility, Acceleration and Offer Rate](/content/dam/munichre/marc/images/2022%20AUW%20Survery%20-%20Table%201%20-%20Eligibility,%20Acceleration%20and%20Offer%20Rate.png/_jcr_content/renditions/original./2022%20AUW%20Survery%20-%20Table%201%20-%20Eligibility,%20Acceleration%20and%20Offer%20Rate.png)
Across the board, we saw a big jump in these key metrics compared to our 2020 survey. See Figure 4 for details on how these metrics trend over time, keeping in mind that the differentiation by human underwriter review was new to the 2022 survey.
Figure 4: Average Eligibility, Acceleration, and Offer Rates Over Time
![Figure 4: Average Eligibility, Acceleration, and Offer Rates Over Time Figure 4: Average Eligibility, Acceleration, and Offer Rates Over Time](/content/dam/munichre/marc/images/Updated%20-%202022%20AUW%20Survery%20-%20Figure%204%20-%20Average%20Eligibility,%20Acceleration,%20and%20Offer%20Rates%20Over%20Time.png/_jcr_content/renditions/original.image_file.1920.1131.file/Updated%20-%202022%20AUW%20Survery%20-%20Figure%204%20-%20Average%20Eligibility,%20Acceleration,%20and%20Offer%20Rates%20Over%20Time.png)
Acceleration Rate Correlations
Finding opportunities to increase eligibility, acceleration, and offer rates are often top of mind for carriers when designing and enhancing their AUW programs. In order to help shed light on areas where we have observed noteworthy correlations with accelerated case throughput, below are commonly shared characteristics of AUW programs with higher acceleration rates:
- Eligibility parameters: Lower face amount limits
- Risk class structure: AUW substandard class availability
- Distribution channels : Multiple AUW sales channels
- Opt-out availability: Mandatory AUW path
- Underwriting tools: More tools/data sources in use
- Monitoring: Post-issue audit methods
Underwriting Tools
Underwriting tools and data source usage are a focal point of Munich Re’s AUW surveys. This year we expanded our answer choices to differentiate between routine and occasional usage of an underwriting tool since newer data sources continue to be introduced in the market but are often limited in how widely they are initially used due to a pilot strategy or low hit rates.
2022 Underwriting Tool Highlights
- All programs continue to use prescription (Rx) drug data and motor vehicle reports (MVR), almost always on a routine basis.
- Nearly all companies have transitioned to using e-applications, while fewer companies are leveraging tele-interviews than in prior years.
- Despite all companies using MIB, only 94% report using the Insurance Activity Index (IAI) product.
- The majority of companies are using non-medical data sources such as identity verification, credit data, credit-based scoring, criminal history, and other public records.
- Fraud/nondisclosure detection is used by just under half of AUW programs.
- Digital health data sources such as electronic health records (EHRs), medical claim records, and aggregated laboratory results are now in use by the majority of AUW programs, although not always on a routine basis.
- The data sources most likely to be used on a non-routine basis are EHRs, followed by aggregated lab results, and other public records.
- Programs continue to refrain from the use of wearable activity data in underwriting, with only a handful of companies evaluating this data source for use in AUW as of 2022.
See Figure 5 for more details on tools and information sources used by companies to triage or classify accelerated cases.
Figure 5: Underwriting Tools and Information Sources used in AUW
![Figure 5: Underwriting Tools and Information Sources used in AUW Figure 5: Underwriting Tools and Information Sources used in AUW](/content/dam/munichre/marc/images/Updated%20-%202022%20AUW%20Survery%20-%20Figure%205%20-%20Underwriting%20Tools%20and%20Information%20Sources%20used%20in%20AUW.png/_jcr_content/renditions/original./Updated%20-%202022%20AUW%20Survery%20-%20Figure%205%20-%20Underwriting%20Tools%20and%20Information%20Sources%20used%20in%20AUW.png)
Digital Health Data Sources
Figure 6: Digital Health Data Sources: Evaluation Versus Usage Over Time
![Figure 6: Digital Health Data Sources: Evaluation Versus Usage Over Time Figure 6: Digital Health Data Sources: Evaluation Versus Usage Over Time](/content/dam/munichre/marc/images/Figure%206.png/_jcr_content/renditions/original./Figure%206.png)
With electronic health records (EHRs) in particular, currently the most common use case in AUW is for triage or kickout to traditional underwriting, followed by post-issue audits, and to a limited extent, in AUW rules engines with human underwriter review. However, in the future, most carriers plan to use EHRs in their AUW rules engines without underwriter involvement. While EHRs have experienced a significant increase in usage over the past several years, they are still being used on an occasional or non-routine basis more so than any other AUW tool and almost always with full review by an underwriter. This is likely a result of the hurdles of getting complete EHR data on a consistent basis.
Given the importance of reliable medical data in the absence of traditional insurance labs and exams, we think it will only be a matter of time before these emerging DHD sources saturate the market, similar to what has already occurred with prescription (Rx) history data.
Summary
As we have seen in our three surveys, AUW usage has expanded across products and risk classes, with face amounts also rising, in part due to the increased demand for fluidless underwriting brought on by the COVID pandemic. Likewise, the underwriting tools and data sources used in AUW decisioning, whether on a routine or ad hoc basis, expanded as well, led by EHRs and medical claims data. New questions in this year’s survey shed light on challenges and current limitations of AUW programs, such as the majority of accelerated decisions still extensively involving human underwriters.
In the future, we expect to see human intervention decline and digital health data sources continue to gain traction as life insurance carriers work towards optimizing their accelerated underwriting programs to issue more policies with faster turnaround times, all while remaining confident in their risk-decisioning process.
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