How AI Underwriting is Challenging Traditional Life Insurance Models
The life insurance industry, which has long relied on human expertise and extensive documentation, is undergoing a significant transformation with the integration of Artificial Intelligence (AI). AI underwriting—where advanced algorithms analyze data and assess risk—has the potential to redefine efficiency, customer experience, and cost structures. But in emerging markets like Sri Lanka, this innovation also raises important questions around accuracy, fairness, and regulatory readiness.
https://www.swissre.com/reinsurance/insights/ai-predictive-underwriting-life-and-health.html
What Is AI Underwriting?
https://www.nmi.com/blog/how-ai-underwriting-is-redefining-risk-management/
AI underwriting uses algorithms to automate the assessment of an applicant’s risk profile. Rather than relying solely on traditional inputs like medical exams and paper forms, AI systems can evaluate:
- Lifestyle and behavioral data
- Wearable health device metrics
- Digital health records
- Historical claim patterns
This shift enables faster approvals, better risk segmentation, and in some cases, straight-through processing (STP) without human intervention.
The Sri Lankan Context: Union Assurance Leads the Way
Sri Lanka’s insurance sector is cautiously exploring the use of AI-powered underwriting. Union Assurance is one of the early adopters, having piloted an AI underwriting model to streamline the life insurance application process. The pilot aimed to:
- Reduce turnaround time
- Improve underwriting consistency
- Enhance the customer onboarding experience.
While the results are still being evaluated, the pilot highlights growing interest among Sri Lankan insurance broker companies and insurers in utilizing digital innovation to remain competitive.
Potential Benefits for Emerging Markets
In developing countries like Sri Lanka, where access to insurance is limited, AI underwriting could:
✅ Make life insurance more accessible by eliminating the need for manual medical checks.
✅ Reduce underwriting costs and premiums through operational efficiency
✅ Personalize risk assessment for underserved populations, including freelancers and gig workers
But It’s Not Without Risks: The Mispricing Challenge
AI systems are only as good as the data they’re trained on. In emerging markets:
- Data gaps in electronic health records can result in biased or inaccurate assessments.
- Algorithms trained on Western datasets may misprice risk in local populations.
- Reliance on non-traditional data (e.g., social media activity or device usage) raises concerns about privacy and fairness.
Inaccurate underwriting could either overcharge low-risk individuals or underprice high-risk applicants, jeopardizing the long-term financial stability of insurers.
Regulatory Watch: Where Does Sri Lanka Stand?
AI underwriting must operate within the legal and ethical frameworks of the local market. Two major regulatory elements are shaping how AI evolves in Sri Lanka:
- Data Protection Act (DPA) of Sri Lanka
The DPA mandates strict guidelines for how personal data, especially health and biometric data—can be collected, processed, and stored. Insurers using AI must ensure that their systems:
- Have explicit user consent.
- Maintain data transparency and security.
- Avoid discriminatory profiling
- IRCSL Sandbox Framework
The Insurance Regulatory Commission of Sri Lanka (IRCSL) has proposed a sandbox environment to allow insurers to test innovative products and technologies. This creates a controlled setting to pilot AI underwriting models without compromising consumer protection.
Human Judgment Still Matters
While AI can handle high volumes and expedite decisions, human oversight remains critical, especially in complex or ambiguous cases. Hybrid models—where AI performs initial analysis and human underwriters make the final call—may be the most practical path forward for Sri Lanka in the near term.
Final Thoughts
AI underwriting presents exciting opportunities to modernize Sri Lanka’s life insurance sector—but it must be approached with caution, especially in emerging markets where data ecosystems and regulatory frameworks are still evolving.
As insurers and insurance broking companies in Sri Lanka experiment with AI, the balance between innovation, ethical use of data, and sound risk pricing will determine whether AI becomes a trusted enabler or a disruptive challenge to the industry’s future.
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