Insurance Curator NEW YORK — Global insurtech firms and traditional life insurance carriers are intensifying investments in automated underwriting to overcome technological barriers that currently prevent the scaling of "instant-issue" policies for high-value death benefits. Despite a surge in venture capital funding for artificial intelligence (AI) and machine learning, industry experts say data fragmentation and algorithmic limitations have kept most instant-approval policies capped at $3 million or less.
The push to automate the underwriting of multi-million dollar policies—traditionally a process involving weeks of medical exams and manual document review—has become the primary focus of the 2026 insurtech funding cycle. According to a January report from the insurance research organization LIMRA, investment in automated underwriting systems (AUS) grew by 22 percent year-over-year as carriers race to meet the demands of high-net-worth consumers who expect digital-first experiences.
“The friction in the high-value life insurance market remains a significant pain point for the industry,” said Marcus Thorne, a senior analyst at the Global Insurtech Institute. “While we have mastered the ability to issue a $500,000 policy in minutes, the risk profile of a $10 million or $20 million policy requires a level of data granularity and medical certainty that current automated systems struggle to replicate without human intervention.”
The Data Interoperability Gap
The primary technological hurdle lies in the lack of standardized, real-time access to comprehensive Electronic Health Records (EHR). For instant-issue policies to scale to high-value benefits, algorithms must ingest and interpret decades of medical history, lab results, and pharmacy records in seconds.
While the 21st Century Cures Act has improved data sharing in the United States, the insurance industry continues to grapple with "data silos." Many hospital systems utilize incompatible formats, making it difficult for an insurer’s AI to build a complete risk profile without manual verification.
“Data is the lifeblood of automated underwriting, but the quality of that data is often inconsistent,” said Sarah Jenkins, Chief Technology Officer at VeroLife, an insurtech firm that recently secured $150 million in Series C funding to address this gap. “To issue a high-value death benefit instantly, you cannot afford a 5 percent margin of error in medical data interpretation. You need near-perfect fidelity, which current OCR [Optical Character Recognition] and NLP [Natural Language Processing] tools are only just beginning to provide at scale.”
Algorithmic Risk and Reinsurance Constraints
Beyond data access, the financial risk associated with high-value policies necessitates the involvement of reinsurers. Reinsurance companies, which provide the capital backbone for life insurers, have historically been hesitant to greenlight fully automated processes for death benefits exceeding $5 million.
The "black box" nature of some AI models creates a transparency issue for reinsurers. To scale, insurtechs must prove that their algorithms are not only fast but also actuarially sound and free from bias.
"Reinsurers are the ultimate arbiters of how high these limits can go," said David Chen, an actuary with the North American Reinsurance Group. "We are seeing a shift where reinsurers are now co-developing proprietary AI models with insurtechs. The goal is to move away from simple 'rules-based' automation to 'predictive' automation, where the machine can accurately forecast long-term mortality risk based on non-traditional data points, such as wearable device metrics and lifestyle patterns."
However, this reliance on non-traditional data has drawn scrutiny from the National Association of Insurance Commissioners (NAIC). In a recent memorandum, the NAIC emphasized that any automated system used for high-value underwriting must be "explainable" and compliant with existing anti-discrimination laws.
The Funding Shift: From UX to Infrastructure
In previous years, insurtech funding largely targeted the user interface (UI) and customer acquisition. The 2025–2026 trend shows a pivot toward the "middle office"—the technical infrastructure that handles risk assessment.
Recent funding rounds for startups like UnderwriteAI and ClearRisk have focused specifically on "automated fluidless underwriting." This technology attempts to replace physical blood and urine samples with digital health markers.
According to data from PitchBook, venture capital investment in life insurance "underwriting tech" reached $4.2 billion globally in 2025. This funding is being used to integrate AI agents capable of querying medical databases, cross-referencing motor vehicle records, and performing real-time fraud detection.
"The industry is moving past the 'gimmick' phase of digital applications," said Elena Rodriguez, a partner at Fintech Ventures. "Investors are now looking for the 'heavy lifters'—the companies that can safely automate a $10 million policy. The first carrier to reliably offer instant-issue at that level will capture a massive segment of the under-served high-net-worth market."
The "Human-in-the-Loop" Hybrid Model
Despite the technological advancements, many industry leaders believe the path to high-value instant issuance will require a hybrid approach for the foreseeable future. This model uses AI to complete 90 percent of the work, with a human underwriter performing a final "sanity check" on high-face-value cases.
"Technological barriers aren't just about the code; they are about the complexity of the human condition," said Thorne. "A $20 million policy often involves complex business ownership, estate planning, and nuanced medical histories that a machine might misinterpret. The 'holy grail' is a system that knows exactly when to automate and exactly when to flag a human."
As of February 2026, several top-tier carriers have begun pilot programs for "near-instant" issue of policies up to $5 million, reducing the turnaround time from 30 days to under 48 hours. While not yet "instant," the reduction in time represents a significant leap forward in solving the friction points that have long plagued the life insurance sector.
Looking Ahead
As AI models become more sophisticated and medical data becomes more accessible through centralized exchanges, the ceiling for instant-issue policies is expected to rise. Analysts predict that by 2028, the technological barriers for policies up to $10 million will largely be resolved for applicants with "clean" digital records.
For now, the industry remains focused on refining the accuracy of automated tools and securing the regulatory approval necessary to bring high-value digital underwriting to the mainstream.
"We are at the precipice of a fundamental shift," Jenkins said. "The question is no longer if we can automate high-value life insurance, but how quickly we can build the trust and data integrity required to do it at scale."