The landscape of life insurance underwriting is undergoing a fundamental transformation, shifting rapidly away from traditional, labor-intensive medical evaluations toward a sophisticated, data-driven paradigm. As insurers face mounting pressure to accelerate policy issuance while maintaining rigorous risk accuracy, the integration of alternative data sources, advanced analytics, and artificial intelligence has become a core operational imperative. To dissect these sweeping industry changes and explore the technological breakthroughs shaping the sector, LexisNexis Risk Solutions is hosting a high-profile industry webinar titled The Evolution of Life Insurance Mortality Modeling. Scheduled for Tuesday, November 10, 2026, at 2:00 PM Eastern Time, the virtual event will convene prominent industry leaders to discuss how carriers can optimize the utilization of comprehensive medical and non-medical information to better understand mortality risk, refine risk segmentation, and achieve greater strategic flexibility.
Background Context of the Event and Industry Transformation
For decades, the life insurance underwriting process relied heavily on traditional requirements, including attending physician statements (APS), paramedical exams, bodily fluids testing, and lengthy manual reviews. While effective at evaluating health status, these traditional methods introduced significant friction into the customer journey, often resulting in weeks or even months of delay before a policy could be issued. In an era shaped by consumer expectations for instant, digital-first experiences—often cultivated by seamless interactions in retail, banking, and property and casualty insurance—the protracted timelines of traditional life insurance underwriting created a notable bottleneck.
Over the past ten years, however, the industry has experienced a gradual democratization and digitization of data. The emergence of electronic health records (EHR), prescription history databases, motor vehicle records, credit-based attributes, and lifestyle data has unlocked new pathways for assessing risk without imposing burdensome requirements on applicants. This shift has given rise to accelerated underwriting programs, where a substantial percentage of applicants are approved rapidly using automated algorithms and predictive models rather than physical exams.
Despite these advancements, insurers face the ongoing challenge of synthesizing disparate data streams into cohesive, reliable underwriting decisions. The sheer volume of available information can lead to data fatigue or analytical silos if not properly managed. Consequently, modern life insurance strategies require advanced modeling solutions capable of harmonizing diverse data inputs, extracting granular risk attributes, and scaling efficiently across various distribution channels. The upcoming LexisNexis Risk Solutions webinar aims to address these exact industry pain points, focusing heavily on the latest iterations of configurable mortality modeling solutions designed to navigate this complex data ecosystem.
The Role of Advanced Analytics and Artificial Intelligence in Mortality Modeling
At the core of the upcoming expert conversation is the technological evolution of predictive modeling. Historically, mortality tables were static, broad-stroke instruments based on generalized population statistics. Modern mortality modeling, by contrast, leverages dynamic, data-driven insights that account for individualized behavioral, financial, and medical markers.
Artificial intelligence and machine learning (AI/ML) have been instrumental in this evolution. Traditional statistical models often struggle with non-linear relationships among variables or the sheer dimensionality of big data. AI-driven modeling techniques, however, can process vast arrays of non-medical and medical data simultaneously, identifying subtle correlations between disparate risk attributes and long-term mortality outcomes that human analysts or legacy systems might overlook.
Furthermore, machine learning algorithms allow carriers to continuously refine their underwriting scorecards. As new data feeds become available and population health trends shift—such as those observed in the wake of global public health events or changing socioeconomic conditions—AI models can adapt more rapidly than static underwriting manuals. This adaptability enables insurers to approach risk segmentation with unprecedented precision, offering competitive pricing to preferred risk applicants while accurately identifying higher-risk profiles that require more nuanced evaluation.
Meet the Expert Panel
The webinar features three distinguished leaders from LexisNexis Risk Solutions, bringing together decades of specialized experience spanning life insurance strategy, product innovation, predictive analytics, and data science.
Justin Baker, Assistant Vice President of Life Underwriting Solutions, brings more than 20 years of insurance industry experience to the conversation. In his current role, Baker leads life insurance market strategy and supports ongoing innovation and product development across the firm’s underwriting solutions portfolio. Prior to joining LexisNexis Risk Solutions, Baker cultivated an extensive background in executive leadership within traditional insurance operations, notably serving as Vice President of Life and Health Administration at COUNTRY Financial. His operational perspective ensures that the discussion remains grounded in the practical realities, regulatory considerations, and strategic goals facing modern insurance carriers.
Christopher Rice, Vice President of Product Management, contributes over 25 years of specialized expertise in insurance data and analytics. Rice oversees a diverse product portfolio that spans multiple insurance markets, focusing on predictive modeling, artificial intelligence, and the translation of complex analytics into actionable business solutions. His work centers on helping organizations harness data architecture to improve operational performance, enhance decision-making frameworks, and streamline enterprise-wide workflows.
Patrick Sugent, Vice President of Data Science and AI, rounds out the panel with deep technical expertise in applying artificial intelligence and machine learning to insurance analytics. Sugent’s professional focus centers on leveraging advanced data infrastructures and predictive modeling techniques to strengthen life insurance risk assessment, accelerate the underwriting continuum, and elevate the overall customer experience through data-driven innovation. His insights will provide attendees with a technical look under the hood of modern mortality modeling algorithms.
Detailed Webinar Agenda and Core Learning Objectives
During the interactive session, the panel of experts will explore several critical themes defining the current and future state of life insurance underwriting:
- Expanding Data Ecosystems: The discussion will examine how insurers can effectively integrate and harmonize an increasingly wide array of medical and non-medical data sources. This includes evaluating the quality, compliance, and predictive power of alternative data streams.
- Granular Risk Attributes: Attendees will learn how more granular risk segmentation allows carriers to move beyond binary or broad risk categories, enabling more tailored pricing and underwriting pathways.
- AI-Driven Modeling Techniques: The panel will break down the practical applications of artificial intelligence and machine learning in mortality modeling, demystifying how predictive algorithms operate within regulatory and compliance boundaries.
- Operational Flexibility: A major focus of the conversation will be how configurable modeling solutions can support diverse life insurance underwriting strategies—ranging from fully automated accelerated underwriting paths to traditional medical underwriting reviews.
Broader Industry Implications and Future Outlook
The discussions at the LexisNexis Risk Solutions webinar reflect broader structural shifts across the global insurance sector. As carriers compete in an increasingly crowded digital marketplace, efficiency and accuracy are paramount. The ability to leverage sophisticated mortality modeling tools directly impacts key financial and operational metrics, including expense ratios, mortality experience, policy issuance velocity, and conversion rates.
From a consumer perspective, the transition toward data-driven underwriting represents a significant qualitative improvement. By reducing the reliance on invasive medical exams and lengthy wait times, insurers can drastically lower friction during the application process. This frictionless experience is particularly crucial for younger demographic cohorts—such as Millennials and Generation Z—who value speed, transparency, and digital accessibility when purchasing financial products.
However, this digital transformation is not without its challenges. As insurers incorporate broader data sets and AI-driven models into their workflows, regulatory scrutiny regarding fairness, transparency, and data privacy continues to intensify. Insurance regulators across various jurisdictions are closely monitoring how predictive models are constructed, ensuring that algorithms do not introduce unintended bias or violate consumer protection laws. Consequently, transparency in modeling—understanding why a model reaches a specific risk conclusion—has become just as important as the predictive accuracy of the model itself.
Event Logistics and Registration Information
The online webinar, titled The Evolution of Life Insurance Mortality Modeling: A Conversation About What’s Next with LexisNexis Risk Classifier, is scheduled for Tuesday, November 10, 2026, beginning at 2:00 PM Eastern Time. Industry professionals, including life insurance executives, underwriting leaders, risk managers, product innovators, and data scientists, are invited to attend.
Registration is currently open through the official online event platform hosted via BigMarker. Interested participants can secure their virtual seats by visiting the registration portal linked through industry distribution channels. The event is hosted by LexisNexis Risk Solutions and shared widely with the insurance industry community through collaboration with InsurTech Express, highlighting the collaborative effort to educate market stakeholders on the technological frontiers reshaping modern risk assessment.
