It is a widely acknowledged industry challenge that Life and Annuity (L&A) carriers grapple with a persistent “clarity gap.” Carriers recognize how overwhelming policyholders find the technical and complex language used in annual statements and other correspondence. Recent research from LIMRA® (2025) reinforces the need for clearer, more effective communication to address this issue.
Life and Annuity carriers must now consider how to use AI-automated correspondence to strengthen policyholder trust while remaining fully aligned with regulatory requirements.
This blog outlines how AI can be harnessed to deliver curated, hyper-personalized communication for Life and Annuity policyholders—driving relevance while building long-term trust and confidence.
Life & Annuity Correspondence: The Current State
- Traditional Life and Annuity correspondence is often designed primarily for regulators, relying on complex actuarial calculations that are disconnected from the average policyholder’s financial understanding.
- Correspondence is largely static, focused on historical information, and lacks prescriptive or forward-looking guidance for policyholders.
- Dense technical terms such as Net Amount at Risk, Exclusion Ratio, and MEC may meet compliance requirements but fail to engage or resonate with policyholders.
- Agents spend significant time explaining basic concepts instead of providing strategic financial guidance.
- The transactional nature of current correspondence contributes to confusion and long-term financial insecurity, increasing the likelihood of policy lapses or terminations.
Leveraging AI-Driven Correspondence for Better Customer Understanding
- From Descriptive to Predictive and Prescriptive Communication
- Hyper-Personalized Messaging Through Contextualization
- Emotionally Aware Interactions for Claims and Service
Then:
Life and Annuity Correspondence for example Annual statements report static or as-is data on historical fund activity, interest rates, guaranteed rates, death benefits, surrender values, and loan details. This helps with providing information, however, fails to provide useful financial insights.
Now:
AI enables interpretation and guidance
Example:
“Your annuity is currently in a higher interest rate period. Initiating a 1035 exchange or rollover at this time could expose you to reinvestment risk at lower rates.”
Personalization is not about flashy technology—it is about delivering timely, relevant, and meaningful experiences.
Then:
Generic values or standard definitions of charges are displayed, such as Market Value Adjustment (MVA) percentages.
Now:
AI can ingest Statements of Additional Information and translate numeric data into plain language based on the policyholder’s specific scenario.
Example:
“If you withdraw funds today, an MVA of $X will apply. This means you may lose $XXX due to current interest rates being higher than when the policy was purchased.”
AI can recognize emotional context, cultural considerations, and situational sensitivity—especially in claims scenarios.
Then:
Standardized, transactional templates request documentation such as death certificates or additional claim details.
Now:
AI can assess beneficiary type (parent, spouse, child, or trust) and dynamically generate empathetic correspondence. Integrated with government databases, AI can also support expedited claims processing.
Example:
“We understand you may be experiencing difficulties obtaining the death certificate. We can guide you through the process or wait until you are ready to proceed.”
Why AI-Automated Correspondence Matters
- Differentiates customer experience and creates competitive advantage.
- Improves retention, enables upsell opportunities, and supports new business growth.
- Combines regulatory compliance with deeper customer engagement and satisfaction.
- Context-aware communication strengthens long-term relationships and amplifies agent effectiveness.
- Creates a flywheel effect—hyper-personalization generates richer data, enabling even more relevant future interactions.
Challenges and Considerations
- Hollow communication: While AI can generate empathetic language, it may lack genuine human emotion. Carriers must determine where a human-in-the-loop is essential.
- Risk of hallucination: AI may generate incorrect projections if not properly constrained. For correspondence, model creativity should be minimized to ensure factual, repeatable outputs.
- Data privacy risks: Carriers must identify PII exposure points and contextual PII risks. Regulations such as the EU AI Act impose strict requirements around purpose limitation and data usage.
- Regulatory evolution: AI governance standards continue to evolve. Under the NAIC AI Model Bulletin, carriers must be able to explain the logic behind any automated correspondence that results in an adverse decision, such as a claim denial.
The Takeaway
AI-driven correspondence is no longer a luxury—it is essential for building policyholder trust and scaling in an increasingly digital insurance landscape. As regulations evolve and generative AI matures, the emphasis will remain on data integrity, transparency, and relevance. The future of Life and Annuity correspondence will be hybrid—combining AI-driven speed and personalization with human oversight to deliver clarity, empathy, and confidence at scale.
Infosys McCamish brings deep experience working with Life and Annuity carriers, supported by an AI-first approach that helps insurers navigate regulatory complexity while accelerating their transition to AI-driven operations.
