SFCR Agentic Workflow
Deploys a **multi-agent AI orchestration system** with six specialized agents that autonomously collect financial data, validate regulatory compliance, generate report narratives, perform quality assurance, and produce XBRL outputs. Human-in-the-loop checkpoints ensure accuracy while significantly reducing report generation time.
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
SFCR Workflow Configuration - Client selection, report type setup, and data source connections for automated report generation
Agent Execution Monitor - Real-time view of AI agents orchestrating data collection, compliance validation, and report generation tasks
Human-in-the-Loop Review - Quality validation interface showing section approvals, compliance checks, and accuracy metrics
Workflow Complete - Executive summary displaying SFCR generation results, time savings, cost reduction, and quality scores
AI Agents
Specialized autonomous agents working in coordination
Orchestrator Agent
Complex SFCR generation requires **coordinating multiple specialized tasks** across data collection, compliance checking, narrative generation, and formatting—with dependencies that must be managed to ensure correct sequencing.
Core Logic
Acts as the **master coordinator** that delegates tasks to specialized agents, manages workflow state transitions, handles inter-agent communication, monitors progress across all phases, and triggers escalations when agents encounter blockers or low-confidence scenarios. Uses a sitemap-based task graph to ensure proper execution order.
Data Collector Agent
SFCR reports require **consolidating data from disparate sources**—financial databases, policy management systems, risk registers, and actuarial models—which is time-consuming and error-prone when done manually.
Core Logic
Autonomously queries connected data sources using specialized tools (`query_financial_database`, `query_policy_database`, `get_risk_assessments`). Validates data completeness, applies transformation rules, and produces structured datasets with data lineage tracking for downstream agents.
Compliance Analyzer Agent
Solvency II mandates strict adherence to **Pillar 1 quantitative requirements** (SCR, MCR, technical provisions) and EIOPA guidelines. Manual compliance verification is resource-intensive and risks regulatory penalties for non-compliance.
Core Logic
Validates all financial calculations against Solvency II requirements using `validate_solvency_calculation` and `check_regulatory_compliance` tools. Cross-references EIOPA guidelines, identifies compliance gaps, generates validation reports with specific references to regulatory articles, and flags items requiring human review.
Report Generator Agent
SFCR narrative sections require **professional financial writing** that accurately represents complex quantitative data, explains risk management strategies, and maintains consistency with regulatory terminology across hundreds of pages.
Core Logic
Generates report sections using **RAG-augmented content creation** with `search_regulatory_knowledge` tool. Retrieves relevant templates, precedent language, and regulatory guidance to produce narratives. Each section includes quality scoring for readability, accuracy, and compliance alignment.
Quality Reviewer Agent
Report quality assurance requires **cross-validating multiple sections** for internal consistency, numerical accuracy, and completeness—a tedious process when performed manually across lengthy documents.
Core Logic
Performs automated validation using `cross_validate_sections` and `calculate_quality_score` tools. Checks for numerical consistency between tables and narratives, identifies gaps in required disclosures, validates terminology usage, and produces quality metrics with specific improvement recommendations.
XBRL Specialist Agent
Regulatory submission requires **XBRL-formatted instance documents** adhering to EIOPA taxonomies. Manual XBRL tagging is highly technical and error-prone, with validation failures causing submission rejections.
Core Logic
Transforms validated report data into XBRL format using `generate_xbrl_tags` and `validate_xbrl_instance` tools. Maps financial facts to correct taxonomy elements, generates instance documents, runs EIOPA validation checks, and produces submission-ready files with comprehensive error logs.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
5 technologies
Architecture Diagram
System flow visualization