LexisNexis Risk Solutions Releases Study Uncovering Hidden Risks and Benefits through the Combination of Medical and Non-Medical Data that can Transform U.S. Life Insurance Underwriting
LexisNexis Risk Solutions has released its 2024 Life Insurance Mortality Risk Management Study, revealing how combining medical and non-medical data can transform life insurance underwriting. The study analyzed data from 50 million individuals over five years, covering 1.7 billion medical claim lines.
Key findings include:
- 10% of applicants with type 2 diabetes and 60% with asthma have average or better-than-average mortality risk
- Integrating medical and non-medical data can reduce mortality slippage and improve decision-making
- This approach streamlines the underwriting process, reducing the need for invasive procedures
The study demonstrates that even within high-risk populations, there are segments suitable for accelerated underwriting, potentially improving the insurance application experience and reaching underserved populations.
LexisNexis Risk Solutions ha pubblicato il suo Studio sulla Gestione del Rischio di Mortalità nell'Assicurazione Vita 2024, rivelando come la combinazione di dati medici e non medici possa trasformare l'underwriting delle assicurazioni sulla vita. Lo studio ha analizzato dati provenienti da 50 milioni di individui negli ultimi cinque anni, coprendo 1,7 miliardi di linee di richiesta medica.
I risultati principali includono:
- Il 10% dei richiedenti con diabete di tipo 2 e il 60% con asma presenta un rischio di mortalità nella media o migliore rispetto alla media
- L'integrazione di dati medici e non medici può ridurre il rischio di mortalità e migliorare il processo decisionale
- Questo approccio semplifica il processo di underwriting, riducendo la necessità di procedure invasive
Lo studio dimostra che anche all'interno delle popolazioni ad alto rischio, ci sono segmenti adatti a processi di underwriting accelerato, potenzialmente migliorando l'esperienza di richiesta dell'assicurazione e raggiungendo popolazioni poco servite.
LexisNexis Risk Solutions ha lanzado su Estudio de Gestión de Riesgo de Mortalidad en Seguros de Vida 2024, revelando cómo la combinación de datos médicos y no médicos puede transformar la suscripción de seguros de vida. El estudio analizó datos de 50 millones de individuos durante cinco años, abarcando 1.7 mil millones de líneas de reclamación médica.
Los hallazgos clave incluyen:
- El 10% de los solicitantes con diabetes tipo 2 y el 60% con asma tienen un riesgo de mortalidad promedio o mejor que el promedio
- La integración de datos médicos y no médicos puede reducir el deslizamiento de mortalidad y mejorar la toma de decisiones
- Este enfoque agiliza el proceso de suscripción, reduciendo la necesidad de procedimientos invasivos
El estudio demuestra que incluso dentro de poblaciones de alto riesgo, existen segmentos adecuados para una suscripción acelerada, lo que puede mejorar la experiencia de solicitud de seguros y llegar a poblaciones desatendidas.
LexisNexis Risk Solutions는 2024 생명 보험 사망 위험 관리 연구를 발표하며, 의료 및 비의료 데이터를 결합하면 생명 보험 언더라이팅을 어떻게 혁신할 수 있는지를 밝히고 있습니다. 이 연구는 5년 동안 5천만명의 개인 데이터를 분석하였으며, 17억 개의 의료 청구 라인을 포함하고 있습니다.
주요 발견 사항은 다음과 같습니다:
- 당뇨병 2형 환자 10%와 천식 환자 60%가 평균 또는 평균 이상으로 사망 위험이 낮다
- 의료 및 비의료 데이터를 통합하면 사망률 감소 및 의사 결정 개선이 가능하다
- 이 접근 방식은 언더라이팅 과정을 간소화하여 침습적인 절차의 필요성을 줄인다
이 연구는 고위험 인구 내에서도 가속 언더라이팅에 적합한 세그먼트가 있으며, 이는 보험 신청 경험을 개선하고 소외된 인구에 접근할 수 있음을 시사합니다.
LexisNexis Risk Solutions a publié son Étude sur la Gestion du Risque de Mortalité en Assurance Vie 2024, révélant comment la combinaison de données médicales et non médicales peut transformer la souscription d'assurance vie. L'étude a analysé les données de 50 millions d'individus sur cinq ans, couvrant 1,7 milliard de lignes de demande médicale.
Les résultats clés incluent :
- 10 % des demandeurs atteints de diabète de type 2 et 60 % d'asthme présentent un risque de mortalité moyen ou meilleur que la moyenne
- L'intégration de données médicales et non médicales peut réduire l'écart de mortalité et améliorer la prise de décision
- Cette approche simplifie le processus de souscription, réduisant le besoin de procédures invasives
L'étude démontre que même au sein de populations à haut risque, il existe des segments adaptés à une souscription accélérée, ce qui pourrait améliorer l'expérience de demande d'assurance et atteindre des populations mal desservies.
LexisNexis Risk Solutions hat seine Studie zum Risikomanagement der Lebensversicherungssterblichkeit 2024 veröffentlicht, die aufzeigt, wie die Kombination von medizinischen und nicht-medizinischen Daten die Lebensversicherungsunterzeichnung revolutionieren kann. Die Studie analysierte Daten von 50 Millionen Personen über fünf Jahre und umfasste 1,7 Milliarden medizinische Leistungsdaten.
Wichtige Erkenntnisse sind:
- 10% der Antragsteller mit Typ-2-Diabetes und 60% mit Asthma weisen ein durchschnittliches oder besseres Sterberisiko auf
- Die Integration medizinischer und nicht-medizinischer Daten kann die Mortalitätsabweichung verringern und die Entscheidungsfindung verbessern
- Dieser Ansatz vereinfacht den Unterzeichnungsprozess und reduziert die Notwendigkeit invasiver Verfahren
Die Studie zeigt, dass selbst innerhalb von Hochrisikopopulationen Segmente vorhanden sind, die für eine beschleunigte Unterzeichnung geeignet sind, was möglicherweise die Erfahrungen bei der Antragstellung für Versicherungen verbessert und unterversorgte Bevölkerungsgruppen erreicht.
- Identification of lower-risk segments within traditionally high-risk populations
- Potential for improved decision-making and reduced mortality slippage
- Opportunity to streamline underwriting processes and reduce costs
- Possibility of reaching underserved populations who need life insurance
- None.
Insights
This study unveils a groundbreaking approach in life insurance underwriting. By combining medical and non-medical data, insurers can now identify lower-risk segments within traditionally high-risk populations. For instance,
The integration of LexisNexis Risk Classifier into underwriting processes could revolutionize risk assessment. This method not only enhances accuracy but also expands opportunities for accelerated underwriting, potentially reducing costs and improving customer experience. The comprehensive analysis of 50 million individuals over 5 years provides robust statistical backing, making these findings highly reliable for industry-wide application.
This study is a game-changer for the life insurance industry. By leveraging both medical and non-medical data, underwriters can now make more nuanced decisions, potentially reducing mortality slippage and improving consistency across the underwriting process. The ability to identify lower-risk individuals within traditionally high-risk groups could lead to more competitive pricing and expanded market reach.
Moreover, the streamlined process could significantly reduce underwriting time and costs, benefiting both insurers and consumers. The potential for increased automation in underwriting traditionally manual cases is particularly exciting, as it could lead to faster policy issuance and improved customer satisfaction. This approach aligns well with the industry's push towards more efficient, data-driven underwriting practices.
This study signals a positive shift for consumers in the life insurance market. The integration of medical and non-medical data could lead to more personalized and fair risk assessments, potentially opening up coverage options for individuals previously deemed high-risk. The reduction in invasive procedures like blood draws and additional medical visits is a significant benefit, making the application process less stressful and more convenient.
However, it's important to ensure that this data-driven approach maintains transparency and compliance with regulations like the Fair Credit Reporting Act. While the potential for faster, less invasive processes is promising, consumers should remain vigilant about their data privacy and understand how various factors influence their insurance options and premiums.
2024 Life Insurance Mortality Risk Management Study shares critical new insights for insurers to improve decision making and enhance automated life applicant reviews, particularly for traditionally high-risk populations with better-than-average mortality risk
Key Findings and Methodology of the Study
- Enhanced Segmentation Beyond What's Commonplace: Even within populations considered high-risk, the study found segments with better-than-average mortality risk who were found to be suitable candidates for accelerated underwriting. For instance,
10% of applicants with type 2 diabetes and60% of those with asthma have average or better-than-average mortality risk. - Improved Decision-Making and More: Leveraging both medical and non-medical data can help carriers reduce mortality slippage, improve consistent decision making across the underwriting process, use structured data to uncover additional automation opportunities, and, ultimately, help improve the close time on the policy process.
- Consumer and Insurer Benefits: Integrating these data sets streamlines the underwriting process and further reduces the need for oftentimes inconvenient and stressful procedures like blood draws and additional medical office visits. This approach benefits insurers by saving time and reducing costs, and benefits consumers by providing a faster, less invasive process that they may be less likely to abandon. Additionally, consumers are afforded greater transparency through the consumer disclosure process and LexisNexis Risk Solutions compliance with the Fair Credit Reporting Act (FCRA).
- Study Methodology: The study analyzed data from a population of 50 million individuals over five years (2018-2022), covering over 1.7 billion medical claim lines, diagnoses, procedures and specialty data.
"Our new study highlights nuanced insights, found through a combination of medical and non-medical data in life insurance underwriting, which reveal that many applicants with conditions traditionally requiring manual review could be candidates for accelerated processes," said Matthew Stull, director of data science, life insurance, at LexisNexis Risk Solutions. "These key new findings have the potential to substantially improve how life insurers assess and triage risk through accelerated underwriting for traditionally high-risk populations with better-than-average mortality risk. By incorporating LexisNexis® Risk Classifier into the life underwriting process, insurers can find cases that would usually require manual review and accelerate them while maintaining accurate risk assessment standards. This is significant because of the benefits for insurers and consumers as it can help reduce costs, improve the overall customer shopping experience and help reach underserved populations who need life insurance."
Notable Findings and Sample Insights: Understanding Medical Risk Profiles
- Type 2 Diabetes: Among 50 million individuals studied,
10% have type 2 diabetes. While traditionally not selected for accelerated underwriting due to a high Standardized Mortality Rate (SMR) of157% , the study found that10% of these individuals could be good candidates for accelerated underwriting by combining medical and non-medical data. - Asthma: With a lower SMR of
114% , asthma represents another condition where data integration can optimize underwriting. The study identified that60% of applicants with asthma could be suitable for accelerated underwriting. - Sleep Apnea: For applicants with sleep apnea, having an SMR of
124% , the study revealed that50% could be candidates for accelerated underwriting when both data sets are considered.
Combining Data for Better Insights
Many life insurance companies often evaluate medical and non-medical data separately, which can lead to missed opportunities for better decision-making when viewed together. While this approach is useful, it may prevent acceleration based solely on medical risk assessments. To address this limitation, a process that simultaneously considers both medical and non-medical data can provide a more comprehensive understanding of an applicant's risk profile.
By leveraging LexisNexis Risk Classifier into life underwriting, which uses non-medical data to generate an insurance score that can be used by carriers to categorize applicants into lower and higher mortality risks, carriers can better identify lower-risk segments that traditional medical data might overlook. This approach supports faster, more accurate decisions, improving the carrier's processes and consumer's experience in applying for life insurance without compromising risk assessment.
Study Methodology
The study analyzed data from a population of 50 million individuals over five years (2018-2022), covering over 1.7 billion medical claim lines, diagnoses, procedures and specialty data. It utilized the LexisNexis Risk Classifier Score, incorporating non-medical data such as driving history, credit records and public records. Standardized Mortality Ratio (SMR) was used to compare mortality risk across various conditions and populations, normalized for gender, age and smoker status.
Download the 2024 Life Insurance Mortality Risk Management Study.
About LexisNexis Risk Solutions
LexisNexis® Risk Solutions harnesses the power of data, sophisticated analytics platforms and technology solutions to provide insights that help businesses across multiple industries and governmental entities reduce risk and improve decisions to benefit people around the globe. Headquartered in metro Atlanta,
Media Contacts:
Chas Strong
LexisNexis Risk Solutions
Phone: +1.706.714.7083
Charles.Strong@lexisnexisrisk.com
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FAQ
What are the key findings of the 2024 LexisNexis Risk Solutions Life Insurance Mortality Risk Management Study?
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