AI in Captive Insurance: Risks, Benefits, and Emerging Coverage Opportunities

Artificial intelligence (AI) is transforming multiple industries, not least the captive insurance market.

AI has the capability to automate and streamline many simple and time- and resource-consuming processes and activities.

The technology can also be used to provide greater and more accurate analysis and insight and, therefore, inform better decision-making.

From an insurance perspective specifically, it can be used in risk management for quantitative data and modeling, and on the administrative side for accounting reports, freeing up underwriters and actuaries to focus more on analysis and other valued-added tasks.

However, it's not without its risks and challenges, namely the potential for errors and bias to creep in when programming or training the algorithm models.

"Captives will face many of the same challenges and risks that all insurers will encounter as AI adoption and implementation continues to progress across the industry," said Tom Prince, principal and consulting actuary at Milliman. "Perhaps most critically, AI amplifies existing risks due to its rapid decision-making, which can spread errors, biases, or vulnerabilities quickly across the organization, leading to more widespread and severe consequences.

"Mitigation strategies should prioritize continuous monitoring and stringent risk management protocols," Mr. Prince continued.

Key Risks

The key risks companies must monitor include algorithmic, cyber-security/data privacy, third-party, and regulatory risks. Algorithmic risks arise when AI models introduce bias, errors, experience degradation (model drift), or lack transparency. In terms of cyber security and data privacy, AI's reliance on large, sensitive datasets heightens exposure to cyber threats and data breaches, while also enabling more sophisticated cyber attacks by bad actors.

Dependence on third-party AI models can introduce vulnerabilities or compliance issues. Regulatory risks stem from the need for AI systems to comply with complex, jurisdiction-specific regulations, particularly regarding antidiscrimination and data protection.

According to Mike Maglaras, principal of Michael Maglaras & Company, predictive AI is widely used by excess insurers and reinsurers to simulate underwriting outcomes, making captives dependent on the credibility of the data produced. Poor or unreliable data, he noted, can lead to coverage restrictions or eliminations.

"Companies that use AI may have more sources of liability now if they are turning over some of their autonomy to a model, especially if they don't fully understand how it works," said Aaron Hillebrandt, principal and consulting actuary at Pinnacle Actuarial Resources. "If, for example, they are using a model that embellishes the data, that can expose them to more liability."

AI Benefits

While AI presents challenges, it offers significant potential for improving risk management, decision-making, and cost efficiency. Specifically, AI can enhance risk assessment and streamline claims processing.

Here are five key areas where AI makes a difference.

• Operational efficiency: Automating tasks with AI reduces costs and frees up resources for strategic initiatives. Off-the-shelf AI tools are readily available for deployment.
• Risk assessment and underwriting: AI improves accuracy by analyzing large datasets, helping captives and their parent companies assess the trade-offs between purchasing commercial coverage and placing risks in the captive.
• Claims management: AI automates claims processing, detects fraud, and enhances customer service through tools like chatbots.
• Regulatory compliance: AI assists in monitoring regulatory changes and supports reporting, which helps reduce compliance risk and human error.
• Risk mitigation: The most notable contribution of AI in captive insurance may be its use of predictive analytics to mitigate losses. By predicting potential hazards, AI helps captive insurers develop proactive risk mitigation strategies, allowing them to address risks in advance and secure more stable financial performance.

While various forms of AI are available, Mr. Maglaras emphasized that only predictive AI is truly valuable for captive insurers. He believes that captives will increasingly need to rely on predictive AI modeling to assess the growing risks of climate change before taking them on.

Captive Coverage

AI presents a significant opportunity for captives to cover the risks it introduces, particularly given their history of insuring nontraditional and emerging risks, where the commercial market may struggle to provide affordable and adequate coverage. However, before insuring these risks, captive managers must ensure they have the proper framework to identify, understand, and manage them.

"Some of the standard coverages that the commercial market provides may have exclusions or restrictions that prevent these risks being covered," said Mr. Hillebrandt. "That's where captives can step in to fill these gaps."

There are four primary risks that captives can address.

• Operational risks: Errors in AI-based decision-making for underwriting, claims, or services can lead to financial loss. Captives can provide errors and omissions (E&O) or business interruption insurance to mitigate these risks.

  Mr. Maglaras added that captives can be used strategically in technology E&O to augment commercial market coverage. Mature captives can plug holes in commercial contracts, assume large deductible exposures on a reimbursement basis, and enhance coverage.

• Cyber-security risks: AI's reliance on large datasets increases exposure to cyber threats. Captives can offer tailored cyber-liability and data privacy insurance to address these evolving risks.
• Regulatory and compliance risks: AI systems must adhere to regulations, but biases or errors can lead to violations. Captives can offer coverage for regulatory defense, fines, and directors and officers (D&O) liability insurance.
• Third-party vendor risks: Failures in third-party AI systems can disrupt operations. Captives can provide insurance for third-party liability and business interruption risks.

"Captives should proactively leverage AI through risk management, allowing parent companies to adopt AI technologies with greater confidence," said Mr. Prince. "By offering customized insurance coverage and risk mitigation strategies for AI-related risks, captives can enable parent companies to experiment with AI at scale while safeguarding against financial and operational impacts.

"This support accelerates AI innovation while managing potential downsides."

Mr. Maglaras also noted that captives will play a crucial role in insuring AI vendors, whether they provide proprietary AI or use third-party products.

Future of AI

Looking ahead, the use of AI and its coverage within captives will continue to expand as the technology advances in both capacity and adoption. As AI risks evolve, captives will play an increasingly important role in providing insurance for failures, data breaches, regulatory challenges, and reputational harm.

"On the coverage side, captives can offer tailored solutions for AI-specific risks like algorithmic bias, model drift, and cyber-security vulnerabilities—emergent risks the commercial market may not adequately cover," said Mr. Prince. "Captives that embrace the risk management aspects of AI adoption can also enable parent companies to innovate with AI while mitigating risk exposure.

"However, the adoption of AI brings downside risks as well. Increased complexity in AI systems can lead to challenges in oversight and management, including difficulties in understanding and mitigating new risks, and remaining in compliance with evolving regulations.

"AI technologies also heighten cyber risks, and captives will need to address greater exposure to potential data breaches and sophisticated cyber attacks."

Mr. Maglaras anticipates an increase in endorsement language, with AI coverage sublimits and additional coverage extensions becoming more common to address AI exposures. He also warned that the growing reliance on AI introduces multifaceted risks for businesses, particularly from the inappropriate, inefficient, or misleading use of the technology.

"Watch for commercial coverage AI exclusions, AI content limitations, and AI-related denial of coverage," said Mr. Maglaras. "Every time this sort of thing has happened over the last 40 years, guess what? Captive capacity has taken up the slack."