How AI and Automation Are Reshaping Captive Insurance Operations

The captive insurance industry is increasingly adopting automation and artificial intelligence (AI) to make processes faster and more efficient.

The technology can help speed up a range of functions, including claims, documentation, and reporting, while easing the administrative burden on professionals and freeing their time for more meaningful tasks.

Yet, despite the strides made so far, certain operations remain highly manual and require human input.

Marcus Schmalbach, CEO of RYSKEX, said that while automation is clearly becoming more common in captive operations, adoption of the technology is still in its relative infancy.

"Most of what we currently see is focused on individual tasks: extracting data, reconciling records, checking documents, preparing reports, or supporting claims administration," said Mr. Schmalbach. "The next step will be to connect these individual tasks into broader workflows across policy administration, claims, finance, and reporting."

Mr. Schmalbach said that the main barrier to adoption is often not the technology itself. Rather, he said, it is the way many captive insurance companies are currently operated.

"A captive can be a highly sophisticated risk-financing vehicle and still be run through spreadsheets, emails, and manually reconciled PDFs," said Mr. Schmalbach. "Information may come from the parent company, broker, fronting [insurer], captive manager, claims administrator, actuary, reinsurer, and auditor, all in different formats and at different points in time.

"That is not primarily an AI problem. It is an operating-model and data problem.

"Captives also tend to have lower transaction volumes than commercial insurers, so historically there has been less economic pressure to invest in fully integrated systems. At the same time, each captive is slightly different, which makes standardization more difficult.

"So the reason many processes remain manual is not that they could not be automated. It is that the underlying processes were often never designed with automation in mind."

Illia Pinchuk, CEO and founder of DICEUS, said that captive operations become difficult at the points where information moves between organizations. A policy may originate with a broker or fronting insurer, claims data may come from a third-party administrator (TPA), and financial transactions may sit in an accounting system. The captive manager still has to bring everything together for the owner, board, auditor, or regulator, he said.

"That is why so much manual work survives, even when individual systems are already digital," said Mr. Pinchuk. "The problem is not necessarily the complexity of each task. It is the lack of continuity between policy, claims, finance, documents, and reporting.

"We saw this directly in one of our captive projects supporting 100 captives and 200 policies. Renewals, endorsements, certificates, invoicing, and reporting were handled through separate processes. A policy renewal could take several days, and certificates were prepared manually. After policy and financial administration were brought into a more centralized environment, renewals could be processed in bulk, ACORD certificates could be generated immediately, and invoicing followed a consistent workflow.

"The practical lesson was that automating one step does not solve the wider problem. The bigger gain comes when the same policy, claim, document, and transaction can move through the operation without being manually reconstructed at every stage. Until that happens, captive professionals remain the integration layer between systems, and too much of their time is spent reconciling information rather than managing risk, capital, and performance."

Key Benefits

AI can deliver several potential benefits for captive insurance programs. The area where it can add the most value, according to Mr. Schmalbach, is by removing administrative noise and giving captive managers better information for the decisions that matter.

"It can help collect and standardize information from different sources, identify missing data, reconcile premium and claims information, compare policy documents and endorsements, monitor deadlines, and prepare initial drafts of board or management reports," said Mr. Schmalbach.

In terms of claims, Mr. Schmalbach said that AI can help classify cases, identify unusual developments, highlight possible duplicates, and prioritize files that require closer attention.

Where finance is concerned, he said that it can help reconcile claims records, bank movements, reserves, accounting entries, and reinsurance recoverables. It can also support scenario analysis around retentions, capital requirements, and reinsurance structures, he said.

"There is also a more strategic use case," said Mr. Schmalbach. "If captive data can be connected with operational data from the parent company, AI can help identify emerging loss patterns or changes in exposure before they become visible in an annual actuarial review.

"However, AI should support decisions, not quietly make them.

"It can identify that a reserve has changed, that a claim looks unusual or that an exposure is deteriorating. A qualified person must still decide what that means, whether coverage applies, and what action should be taken."

Mr. Pinchuk said that the AI opportunity in captive insurance was threefold: document automation, an operational copilot that can work across connected data, and controlled AI agents that can perform routine actions within clearly defined permissions.

"Today, the immediate value is largely in the first two stages," said Mr. Pinchuk. "A captive manager may receive a renewal policy or endorsement from a fronting [insurer] and need to identify changes in limits, deductibles, insured entities, premiums, or effective dates. AI can extract those fields, compare them with the expiring record, and show the manager only what changed. The professional reviews the exceptions instead of rereading the entire document."

In captive insurance, Mr. Pinchuk said that AI's value is amplified by the number of parties involved in operating a program. A single management question, he said, may require information from the captive manager, TPA, broker, fronting insurer, accounting system, and historical policy documents. AI can help assemble that context, identify inconsistencies, and prepare the information for professional review, he said.

"Technology is most effective when it reduces the amount of material a professional has to process before reaching the actual decision," said Mr. Pinchuk. "In underwriting, systems consolidate submission data and surface exceptions. In claims, automation can classify documents and route a case to the right specialist.

"For captives, the opportunity goes beyond document extraction. AI can support claims anomaly detection, identify policies approaching renewal, highlight financial mismatches, find claims nearing a reinsurance attachment point, or prepare a traceable first draft of a board report.

"The next step is not simply asking AI questions about captive data. It is allowing AI agents, within clearly defined permissions, to coordinate routine work across policy, claims, finance, and document systems while keeping professionals in control of consequential decisions."

Julie Bordo, president and CEO of PCH Mutual, said, "Having a full enterprise system that offers a single source of truth for all captive operations from application to rate, quote, bind, to claims reporting, and management, and incorporates AI into its system, is the most efficient way to improve captive management. Such a system allows the captive and its service providers to access, process, and share a captive's material data seamlessly."

Role of the AI Agent

AI agents can play a key role in running a captive insurance company, particularly in operational coordination. For example, an agent could request missing information, check whether a claim submission is complete, reconcile data across systems, prepare a draft report, follow up on missing bordereaux, or escalate an issue when a defined threshold has been reached. Such uses could materially reduce the time spent moving information between parties and systems.

The key question when it comes to AI agents, Mr. Schmalbach said, is not whether the technology can perform a task, but what authority it has been given.

"An agent may identify that a claim exceeds a reporting threshold and prepare the relevant notification," said Mr. Schmalbach. "It should not independently deny the claim, change a reserve, or approve a material payment.

"The same applies to financial processes. An agent can prepare a payment instruction or identify an inconsistency, but it should not be able to move funds outside clearly defined approval controls.

"Every action should be logged and capable of being reviewed. There must also be clear escalation points and a person who remains accountable."

Steve McElhiney, vice chairman and chief commercial officer of Piko Labs AI, said that agentic AI will transform captive insurance from a system of record into a system of action. AI agents, he said, will autonomously monitor routine workflows and, eventually, provide real-time monitoring of individual captives.

"Routine matters such as board materials, correspondence, and other similar tasks will all be automated," said Mr. McElhiney. "Efficiencies will be enhanced, governance improved, and the entire captive ecosystem will achieve greater scale."

Adoption Requirements

Despite the potential benefits of AI and automation, several key practices need to be put in place before adoption. Initially, Mr. Schmalbach said, policy, claims, and financial information must be connected through a consistent structure. Policies, insured entities, claims, payments, reserves, and reinsurance recoveries all require stable identifiers and reliable timestamps.

Key terms for important policy information such as limits, deductibles, triggers, exclusions, and endorsements need to be available as structured data, said Mr. Schmalbach.

Claims data also needs to be consistent, said Mr. Schmalbach. Reported, paid, incurred, and reserved amounts must be clearly distinguished, and changes over time must be traceable, he said.

The same applies to financial information, said Mr. Schmalbach. If the parent company, captive manager, claims administrator, and fronting insurer all use different classifications, AI will simply process inconsistent information more quickly, he said.

"Captives also need to know where data came from, when it was changed, and who owns it," said Mr. Schmalbach. "Access rights, version control, cybersecurity, and data retention are therefore part of the AI discussion, not separate from it.

"A lot of historical data will need to be cleaned before it becomes genuinely useful. Putting old spreadsheets, policy documents, and claims files into an AI system does not automatically create reliable intelligence.

"In practical terms, the captive and its operating partners need to agree on a common data structure and clear responsibilities for maintaining it."

Ms. Bordo said that all parties must first build trust. Rather than proceeding with swift implementation and blind trust, she said, AI adoption involves a comprehensive review of systems, research into the possibilities it offers, and implementation and testing tailored to the operational needs of the particular captive.

"PCH has implemented AI into many areas of operation, and we have humans overseeing these processes," said Ms. Bordo. "We are also constantly looking for the opportunities AI has unearthed to continue improving all aspects of our operations."

Support, Not Replacement

Rather than replacing people, AI should be used to complement and support them by removing repetitive and labor-intensive work that can be performed by a machine and making exceptions visible. That approach enables professionals to focus on more important areas where they can add value and make better-informed decisions.

"A captive manager should not have to review every transaction manually simply because the systems cannot distinguish between routine activity and something that requires judgment," said Mr. Schmalbach.

"The technology should identify where information is missing, where a threshold has been exceeded, or where a claim, payment, or exposure is behaving differently from what was expected.

"That allows captive managers to spend more time on the work where their experience matters: interpreting coverage, challenging assumptions, advising boards, dealing with regulators and auditors, and negotiating with insurers and reinsurers.

"The principle should be fairly simple: The system can recommend, but the professional must decide.

"Human oversight should also not be treated as a final check added at the end of an automated process. Approval rights, decision thresholds and four-eyes controls need to be built into the process from the start.

"Technology can also help reduce key-person risk. A great deal of captive knowledge still sits in individual inboxes or in the experience of one or two people. Making decisions, assumptions, and previous outcomes searchable can be extremely valuable."

Mr. Pinchuk said that captive management should follow the same principle as underwriting, where technology can gather submission information, apply rules and highlight unusual risks, but the underwriter remains responsible for the decision. The same applies to claims, he said: Systems can organize documents, identify missing information, and route cases, while coverage interpretation and settlement decisions remain with claims professionals.

"The practical boundary is relatively clear," said Mr. Pinchuk. "High-volume, repeatable, and auditable work can be automated more extensively. When a decision affects coverage, capital, regulation, governance, or material financial outcomes, AI should prepare the information or recommendation while the professional retains approval and accountability.

"This opens up much more useful applications than simply generating summaries. AI can reconcile claim payments against accounting records, detect unusual loss development, identify exposure concentrations, prepare renewal comparisons, and assemble draft board reporting from trusted captive data. Every material AI insight should be explainable and traceable back to the underlying captive data.

"That also changes the operating model. Instead of professionals reviewing every routine transaction, technology can process normal activity and bring forward the cases that require attention. A manager can focus on a deteriorating loss trend, an unexpected reserve movement, a missing reinsurance recovery, or an inconsistency between a [insurer] document and the approved program structure.

"Technology adoption should therefore be measured by operational outcomes rather than headcount reduction. Shorter renewal cycles, fewer reconciliation errors, faster access to current information, clearer audit trails, and better management of exceptions are more useful indicators.

"The biggest opportunity for AI in captive insurance is not replacing captive managers. It is moving them from managing transactions to managing exceptions. When policy, claims, and financial data are connected, AI can do much of the preparation and reconciliation work while professionals retain control over the decisions that require judgment and accountability."

Mr. McElhiney said that AI and related technologies will not replace captive management firms because a captive still requires sophisticated human involvement from an array of service providers and captive management teams. Rather, he said, the technology will enhance the captive management firm's role, enabling it to handle double or triple the number of captives.

"The jobs themselves will transform to focus more on proactive solutions and analytical efforts," said Mr. McElhiney. "I strongly believe that, through AI and related automation, the captive industry will undergo an unprecedented level of growth and reinsurance utilization by captives will soar."

Ms. Bordo said, "The best solution is if captive managers used AI to prepare the financials, spreadsheets, and forms; analyze data; and streamline the accounting and bookkeeping processes so the captive manager can spend more time deep thinking and preparing strategies to provide solutions and plans to improve the business to proactively serve their clients. Captive managers should be transparent about how they use AI to the benefit of their clients and then demonstrate this benefit by proactively contacting the client and offering consulting services."

Future Developments

The next step in the evolution of captive management data, Mr. McElhiney said, is not simply automating existing workflows; it is creating an intelligent operating layer—a unified view—across the captive ecosystem.

"Our SaaS product is focused on using AI for enhanced data ingestion and providing a unified view of disparate data sources in one cohesive and integrated manner," said Mr. McElhiney. "AI can continuously reconcile data from multiple stakeholders, generate management reports, surface emerging risk trends, and provide actionable insights in real-time.

"Our product also allows captive management firms to scale their businesses more significantly, leveraging existing resources to grow the number of captives under management and support entirely new captive structures. It will bring utilization by captives to a much greater level, and new forms of risk will find capacity.

"Greatly enhanced data fundamentally allows for more optimal risk retention and risk transfer placements with more precise premium outcomes. It is a game changer for the global captive insurance industry."