Multi-Agent Based Automation of Reinsurance Placement Support

This primary agent ingests the fully underwritten primary risk from the Policy Administration System (PAS). It analyzes exposure concentrations, probable maximum loss (PML), and attachment points against current treaty wordings. Using retrieval-augmented generation (RAG) over the treaty database, it drafts a concise cession summary highlighting key risk factors, required capacity, and recommended session structure for underwriter review. This automates the manual compilation of placement memos, saving 2-3 hours of analyst work per large risk.

A rules-based agent cross-references the cession summary against a live database of reinsurer treaties, facultative agreements, and current market appetite signals (often from external market platforms). It scores and ranks potential markets based on alignment with peril, geography, remaining capacity, and historical performance. The engine prepares a shortlist with recommended placement tiers, automating the manual market research that typically delays placement by days.

Upon underwriter approval, this orchestration agent triggers the automated assembly of the formal bordereau. It pulls validated data points from the PAS and cession summary, formats them to market-specific templates (often Excel or XML), and attaches supporting documentation. The agent then submits the package via secure API to reinsurer portals or via email, with full tracking and receipt confirmation. This eliminates error-prone manual data entry and version control issues in bordereau creation.

A persistent monitoring agent tracks all outstanding submissions, polling for acknowledgments, queries, and quotes from reinsurer systems. It logs all communications and status changes in the reinsurance placement module. For exceptions—like non-standard terms or capacity shortfalls—it classifies the issue and routes it with full context to the appropriate human underwriter queue in tools like ServiceNow or Jira. This ensures no placement stalls unnoticed and provides full auditability.

For facultative placements requiring new contract wording, a specialized legal agent assists. Using RAG over a library of precedent slips and clause wordings, it generates a first-draft slip based on the agreed terms. The agent highlights non-standard clauses for review and ensures consistency with master agreements. This reduces legal drafting cycles from days to hours and minimizes back-and-forth with reinsurers' legal teams.

The foundational component that connects agents to core enterprise systems. It uses a combination of APIs (for modern PAS like Guidewire), middleware, and robotic process automation (RPA) for legacy mainframes to bi-directionally sync data. This layer ensures the workflow reads from the single source of truth (the PAS) and writes back bound reinsurance placements, premium allocations, and commission details to the general ledger and reinsurance administration system, closing the operational loop.

The primary underwriter drives the workflow by submitting large or complex risks that exceed retention limits. They benefit from agents that automatically analyze the risk, prepare a structured cession summary, and identify optimal treaty/facultative markets based on current capacity, freeing up 60-80% of the time traditionally spent on manual placement preparation. This allows them to bind more primary business and focus on structuring deals.

This role benefits from standardized, auditable workflows that replace ad-hoc email and spreadsheet processes. The automation ensures bordereaux are formatted correctly, submission packets are complete, and all placement actions are logged in the reinsurance system (e.g., Sequel, RI3K). This reduces operational errors, improves compliance with treaty reporting deadlines, and provides real-time visibility into the placement pipeline.

These specialists act as a quality gate and strategic beneficiary. The system routes pre-vetted cession packages to their queue with recommended markets and terms. They review the agent's analysis, apply nuanced market relationships, and make the final placement decision. The automation handles the data assembly, allowing them to focus on negotiation and securing the best terms, improving placement economics.

The CUO is the strategic and financial driver, mandating automation to improve portfolio management and reinsurance economics. They benefit from aggregated data on placement patterns, cost trends, and market capacity utilization generated by the workflow. This enables more strategic reinsurance purchasing, better aggregate risk management, and direct improvements to the combined ratio through optimized cession costs.

This team owns the implementation of the agentic orchestration layer (e.g., using LangGraph). They integrate with core policy systems, document stores, and external market data feeds. Their success is measured by system reliability, seamless data flow, and maintaining a clear audit trail. The workflow reduces their long-term support burden by replacing fragile, manual integration points with a governed, observable automation platform.

This function acts as a critical governance gatekeeper. They define the rules for the agents, ensuring placements adhere to internal authorities, treaty wordings, and regulatory requirements (e.g., collateral, side letters). The workflow benefits them by embedding these rules into the automation logic, creating an immutable decision log, and flagging non-standard terms for mandatory review, thereby reducing regulatory and contractual risk.