Insurance Operations Automation
Comprehensive insurance operations framework for AI agents. Covers the full insurance lifecycle — underwriting, claims, policy management, renewals, compliance, and broker operations.
About this skill
This AI agent skill offers a robust framework designed to guide AI agents through the complexities of insurance operations. It covers the entire insurance lifecycle, including detailed workflows for underwriting assessment, claims processing, policy administration, and broker operations. The skill incorporates industry benchmarks, regulatory requirements from various jurisdictions (US, UK, EU), and automation priorities to ensure efficient and compliant operations. Users can leverage this skill to empower their AI agents with deep domain knowledge and structured processes for tasks such as risk scoring, fraud detection, quote generation, policy renewals, and regulatory verification. It provides specific metrics and triggers, like combined ratio targets for underwriting, severity triage for claims, and retention probability models for renewals, enabling AI to make informed decisions. The primary use case is to enhance the efficiency and accuracy of insurance processes, reducing manual effort and ensuring adherence to compliance standards. It helps automate repetitive tasks, provides structured decision-making criteria, and facilitates consistent execution across various insurance functions, ultimately improving operational performance and customer experience.
Best use case
The primary use case for this skill is to automate and optimize core insurance workflows, significantly boosting efficiency and compliance for insurance carriers, brokers, and underwriters. AI agents utilizing this skill can handle a wide array of tasks from initial risk assessment and policy issuance to claims processing and regulatory reporting, reducing operational costs and human error while ensuring adherence to complex industry regulations.
Comprehensive insurance operations framework for AI agents. Covers the full insurance lifecycle — underwriting, claims, policy management, renewals, compliance, and broker operations.
Users should expect automated, efficient, and compliant execution of various insurance operations tasks, leading to reduced manual effort, faster processing times, and improved decision-making.
Practical example
Example input
Assess a new auto insurance application for John Doe, policy type 'standard', vehicle 'Toyota Camry 2023', claims history 'none', credit score 'excellent'. Provide risk score, data enrichment checklist results, and combined ratio target.
Example output
Underwriting Assessment for John Doe (Auto): Risk Score: 8.5/10 (low risk). Data Enrichment: Credit (verified), Claims History (verified), Property Data (N/A), Telematics (N/A). Combined Ratio Target: 96%. Referral: None (within auto-approve limits).
When to use this skill
- When automating complex insurance underwriting processes, including risk scoring and data enrichment.
- When streamlining claims processing, from FNOL intake to severity triage and subrogation identification.
- When optimizing policy administration tasks such as quote-to-bind, renewals, and mid-term adjustments.
- When ensuring comprehensive regulatory compliance across multiple jurisdictions (US, UK, EU) and detecting potential fraud.
When not to use this skill
- For general business process automation unrelated to insurance-specific workflows.
- If the organization lacks the infrastructure or data to support AI-driven insurance automation.
- If precise, real-time human judgment is absolutely critical for every decision point without AI assistance.
- For tasks requiring highly subjective, nuanced negotiation not covered by defined frameworks.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/afrexai-insurance-automation/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Insurance Operations Automation Compares
| Feature / Agent | Insurance Operations Automation | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | hard | N/A |
Frequently Asked Questions
What does this skill do?
Comprehensive insurance operations framework for AI agents. Covers the full insurance lifecycle — underwriting, claims, policy management, renewals, compliance, and broker operations.
How difficult is it to install?
The installation complexity is rated as hard. You can find the installation instructions above.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Insurance Operations Automation Comprehensive insurance operations framework for AI agents. Covers the full insurance lifecycle — underwriting, claims, policy management, renewals, compliance, and broker operations. ## What This Skill Does Guides your AI agent through insurance-specific workflows with industry benchmarks, regulatory requirements, and automation priorities. ## Capabilities ### 1. Underwriting Assessment - Risk scoring framework (12 factors, weighted by line of business) - Data enrichment checklist (credit, claims history, property data, telematics) - Referral triggers and authority limits by tier - Combined ratio targets by line: Auto (95-98%), Home (85-92%), Commercial (88-95%), Life (varies by mortality table) ### 2. Claims Processing Pipeline - FNOL intake automation (voice + digital, structured extraction) - Severity triage: Green (auto-approve <$2K) → Yellow (adjuster review $2K-$25K) → Red (SIU referral >$25K or fraud indicators) - Subrogation identification triggers - Reserve estimation formulas by claim type - Settlement authority matrix ### 3. Policy Administration - Quote-to-bind workflow (target: <15 min for personal lines) - Mid-term adjustment processing - Renewal scoring: retention probability model (7 factors) - Cancellation/non-renewal compliance by state/jurisdiction ### 4. Broker Operations (Jointly AI Model) - 5-agent pipeline architecture: Intake → Research → Quoting → Analysis → Delivery - Market panel management and placement optimization - Quote comparison normalization across carriers - FCA/state regulatory compliance verification - Parallel execution: up to 4 simultaneous carrier interactions ### 5. Compliance & Regulatory - **US:** State DOI requirements, NAIC model laws, Solvency II (reinsurers) - **UK:** FCA handbook (ICOBS, SYSC), Consumer Duty, IDD compliance - **EU:** Solvency II, IDD, GDPR for policyholder data - Anti-fraud indicators (SIU trigger list — 15 red flags) - SAR/suspicious activity reporting thresholds ### 6. Insurance Metrics Dashboard | Metric | Personal Lines Target | Commercial Target | |--------|----------------------|-------------------| | Combined Ratio | 95-98% | 88-95% | | Loss Ratio | 60-70% | 55-65% | | Expense Ratio | 25-32% | 28-35% | | Claims Settlement Time | <48h (auto) | <14 days | | Policy Issuance Time | <15 min | <24h | | Renewal Rate | >85% | >80% | | Quote-to-Bind Ratio | >25% | >15% | | NPS | >40 | >35 | ### 7. Automation Priority Matrix | Process | Hours/Month (50-person broker) | Agent-Ready? | Expected Savings | |---------|-------------------------------|--------------|-----------------| | Quote comparison | 160h | Yes — now | $140K-$280K/yr | | FNOL intake | 120h | Yes — now | $105K-$210K/yr | | Policy document generation | 80h | Yes — now | $70K-$140K/yr | | Renewal processing | 100h | Yes — now | $87K-$175K/yr | | Compliance checks | 60h | Yes — now | $52K-$105K/yr | | Subrogation identification | 40h | Partial | $35K-$70K/yr | | Complex claims adjustment | 200h | Human-in-loop | $50K-$100K/yr | ### 8. Insurance-Specific Agent Prompts **Underwriting Agent:** ``` You are an underwriting assessment agent. For each submission: 1. Extract all risk factors from the application 2. Score each factor against the risk matrix (1-10 scale) 3. Calculate composite risk score (weighted by line of business) 4. Flag any referral triggers (prior losses >3 in 5yr, credit <600, high-hazard occupation) 5. Recommend: Auto-approve / Refer to senior / Decline with reason 6. Generate underwriting memo with supporting data ``` **Claims Triage Agent:** ``` You are a claims triage agent. For each FNOL: 1. Extract: date of loss, type, description, estimated amount, policyholder details 2. Verify active coverage and applicable endorsements 3. Assign severity: Green (<$2K auto-process) / Yellow ($2K-$25K adjuster) / Red (>$25K or fraud flags) 4. Check fraud indicators against the 15-point SIU trigger list 5. Set initial reserve based on claim type benchmarks 6. Route to appropriate handler with priority score ``` ## 90-Day Deployment Roadmap **Month 1:** Deploy intake + quote comparison agents. Target: 70% of personal lines quotes handled autonomously. **Month 2:** Add claims triage + policy document generation. Target: FNOL processing <5 minutes, auto-approval for Green claims. **Month 3:** Compliance monitoring + renewal automation. Target: 85%+ renewal rate, zero compliance gaps. ## Cost Framework - **Solo broker/MGA:** $2K-$5K/month (2-3 agents) - **Mid-size broker (20-50 staff):** $5K-$15K/month (5-8 agents) - **Carrier/large broker (100+ staff):** $15K-$50K/month (10-20 agents) ## Resources - **Calculate your insurance automation ROI →** [AI Revenue Leak Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/) - **Full Insurance & Fintech Context Pack →** [AfrexAI Context Packs](https://afrexai-cto.github.io/context-packs/) — $47, includes fintech agent configurations, compliance frameworks, and industry benchmarks - **Configure your insurance agent stack →** [Agent Setup Wizard](https://afrexai-cto.github.io/agent-setup/) - **Bundle:** Pick 3 packs for $97 | All 10 for $197 | Everything $247
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