Analysis of 76 insurer and reinsurer financial and regulatory filings finds AI-generated and manipulated evidence absent from discussions of claims and underwriting

CHEVY CHASE, Md., Sept. 3, 2026 /PRNewswire/ — Clearspeed, the global leader in voice-based risk assessment, today released new research examining the growing challenge for insurers to move faster with AI and automation while determining whether the information those systems act on can be trusted.

The Speed of Trust: Building the Trust Intelligence Layer for Insurance in the Age of Agentic AI, commissioned by Clearspeed and independently authored by insurance innovation strategist Sabine VanderLinden, CEO of Alchemy Crew Ventures, draws on a review of 76 public filings from 49 insurers and reinsurers, 31 industry studies, and 16 interviews with claims and underwriting leaders at insurance companies across the United States and United Kingdom.

The research identifies a paradox emerging as insurers rapidly adopt AI and automation: the industry is automating decisions, handoffs, evidence review, and customer interactions faster than it is building the infrastructure needed to clear those interactions confidently. Simultaneously, AI is making it faster and easier to create convincing false or manipulated photos, documents, voices, and identities that can enter insurance workflows.

Reserving Against A Risk Not Yet Named

“Industry research published in March 2026, based on a survey of 300 U.S. insurance claims professionals, found that 98% agree AI editing tools are driving a rise in digital media fraud, while just 32% say they are very confident they could identify a deepfake.”

“That is the verification gap: the distance between what the industry can see coming and what it can currently detect,” said VanderLinden. “Insurance is automating decisions faster than it can verify the information behind them.”

Alchemy Crew Ventures researchers searched 76 annual reports, 10-K filings, proxy statements, and statutory returns from 49 insurers and reinsurers for a dozen terms related to AI-generated and manipulated evidence, media, and imagery. The analysis found:

• Zero mentions of synthetic media, synthetic identity, or voice cloning across all 76 filings
• Just six of 49 companies mention deepfakes — and only as a cybersecurity concern, never in connection with evidence used in claims or underwriting decisions
• Five of the world’s top 10 reinsurers were analyzed; none mention deepfakes, synthetic media, or AI-generated evidence in their most recent annual reporting

“There is a striking gap between where this risk is discussed and where capital is committed,” said VanderLinden. “In the filings that set reserves, uncertainty, litigation pressure, and adverse development are all named. The trust problem beneath them is not.”

Genuine Customers Are Paying the Price

Most claimants are genuine. According to the Coalition Against Insurance Fraud, fraud accounts for roughly 10% of property and casualty losses, with the trust deficit draining at least $308.6 billion annually from the U.S. insurance system. 

But the deeper issue is not simply the cost of fraud alone. Until insurers have a consistent way to determine which interactions need speed, scrutiny, or human judgment, the industry pays for trust twice: once through leakage from the few bad actors, and again through friction imposed on the genuine majority.

“90%+ of customers who make a claim are honest, good people for whom we should be just sorting out their service needs as quickly as possible,” Ian Thompson, former Group Chief Claims Officer at Zurich Insurance, told researchers. “But how many of those genuine customers get the feeling that they’re not being trusted, because we’re trying to catch the other 10%?” 

Making the Trust Intelligence Layer Operational

In the report, VanderLinden argues that insurers should work to address this challenge by making trust a measurable infrastructure layer across the policyholder journey. 

Rather than using more AI merely to catch more fraud, insurers should establish a Trust Intelligence Layer: a continuous, regulator-ready risk indicator running across the policyholder journey that is designed to help insurers clear the genuine majority quickly while directing human judgment to the exceptions.  

The signal informs a decision rather than making one, produces an audit trail rather than an automated denial, and does not require demographic or historical knowledge of the individual being assessed.

“In the age of agentic AI, deepfake evidence, embedded distribution, and automated workflows, insurers can no longer treat trust as a soft value or a late-stage consideration. The opportunity for carriers is to establish trust earlier and make it a measurable operating layer across the policyholder journey,” said VanderLinden.

“Trust is our most vital currency: it is the hardest thing to gain and the easiest thing to lose,” said Alex Martin, co-founder and CEO of Clearspeed. “Today’s promise of AI should yield a faster, richer experience for genuine customers, but that must begin with verifying where to extend trust.”

Vision 2030: Trusting the Conversation

The report also looks ahead to 2030, when a material share of insurance interactions will be agent-to-agent: a customer’s AI agent transacting with an insurer’s AI agent, at machine speed, with no human in the loop for routine business. In that world, the verification question does not disappear; it migrates and intensifies. When the action is always executed correctly, the question left is whether the interaction behind it can be trusted.

The report describes this as a shift in what gets verified, not whether verification is still needed. As more insurance interactions become AI-to-AI, the human input behind each transaction — the information a person provides, however it enters the system — still has to be trusted before automated systems act on it. The report argues insurers will need an auditable way to establish that trust at the moment of interaction. The organizations that build that capability now, while the interactions are still human-led, will define the standard when those interactions become machine-to-machine.

The report concludes that “the arms race is symmetrical. The only durable advantage is to establish trust earlier and faster than the adversary can manufacture doubt.” 

The Speed of Trust: Building the Trust Intelligence Layer for Insurance in the Age of Agentic AI is available here.

About Alchemy Crew Ventures

Alchemy Crew Ventures is an enterprise AI and insurance transformation advisory firm led by Sabine VanderLinden. Founded in 2020, the firm advises insurers, reinsurers, big tech, tech ventures and institutional investors on translating emerging technology capability into measurable portfolio outcomes. VanderLinden brings over 28 years of insurance and financial services experience.

About Clearspeed

Founded in 2016, Clearspeed is the global leader in voice-based risk assessment. Its proprietary technology detects the level of risk in a person’s voice based on vocal characteristics universal to all humans—enabling faster, more confident decisions. Initially developed for the U.S. Department of Defense, Clearspeed quickly exposes indicators of risk for government and military agencies in high-stakes environments. Commercially, it helps insurers, financial institutions, and other enterprises assess risks like fraud and insider threats, unlock operational savings, and elevate the customer experience. With broad applications, Clearspeed delivers bias-free, highly precise, individual risk assessment wherever achieving trust at scale is essential.

With offices in the Washington, D.C. area, San Diego, and internationally, Clearspeed is used in 37 countries and supports over 60 languages. The company has earned more than 30 industry awards, including CNBC’s World’s Top InsurTech Companies. Learn more at www.clearspeed.com.

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SOURCE Clearspeed