analyzing-property-casualty-lines
Evaluates P&C insurance lines with market cycle analysis, loss cost trending, and competitive assessment.
Skill by casemark
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/fdu-ins-analyzing-property-casualty-lines
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/analyzing-property-casualty-lines
What's inside
- Skill name
analyzing-property-casualty-lines- Description
- Evaluates P&C insurance lines with market cycle analysis, loss cost trending, and competitive assessment. Use when analyzing P&C markets, tracking insurance cycles, or evaluating line profitability.
- License
- Apache-2.0
- Metadata
- author: casemark
- Instructions
- 73 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Analyzing Property Casualty Lines ## When To Use - Evaluating profitability and underwriting performance of specific P&C lines (commercial auto, GL, property, workers' comp, professional liability, etc.) - Tracking market cycle position (hard vs. soft market) for pricing and capacity decisions - Performing loss cost trending to project future loss development - Assessing competitive positioning within a line or geographic market - Supporting reinsurance purchasing decisions with line-level performance data - Preparing portfolio reviews for underwriting committees or investor reporting ## Inputs To Gather - **Line-of-business data**: Written premium, earned premium, incurred losses (paid + reserved), ALAE/ULAE splits, policy counts by line - **Loss triangles**: Accident-year or policy-year development triangles (paid and incurred) with a minimum of 5–10 development periods - **Rate change history**: Rate filings, rate adequacy studies, or renewal rate change tracking by quarter - **Expense data**: Commission rates, acquisition costs, general expenses, and combined ratio components - **Market benchmarks**: Industry combined ratios, rate-on-line indices, AM Best or S&P segment reports, ISO/NCCI aggregate data [VERIFY: benchmark availability varies by line and jurisdiction] - **Catastrophe exposure**: PMLs, AALs, or cat model output for property-exposed lines - **Regulatory context**: Rate filing requirements, prior-approval vs. file-and-use status by state [VERIFY: filing requirements by state and line] ## Workflow 1. **Define scope and segmentation** - Identify target lines (e.g., commercial property, general liability, personal auto) - Set the analysis period (typically 5–10 accident years for trend credibility) - Determine segmentation: by state, policy size, distribution channel, or coverage sub-type 2. **Develop loss costs** - Select development method (chain-ladder, Bornhuetter-Ferguson, or Cape Cod) based on data maturity and volatility - Apply loss development factors to bring immature years to ultimate - Trend historical losses to prospective cost level using loss cost trend factors (severity + frequency) - Adjust for one-time events: strip out or cap large losses, isolate catastrophe losses from attritional - On-level earned premiums to current rate levels to enable apples-to-apples comparison 3. **Analyze market cycle position** - Plot historical combined ratios and rate changes over 10+ years to identify cycle phase - Compare current rate adequacy to indicated loss costs — gap signals where the cycle is heading - Assess supply-side indicators: carrier entries/exits, capacity changes, reinsurance pricing shifts - Evaluate demand-side factors: exposure growth, insured value inflation, emerging liability trends - Classify current position: hardening, hard, softening, or soft, with supporting evidence 4. **Perform competitive assessment** - Benchmark combined ratio, loss ratio, and expense ratio against top-5 and industry-average peers - Identify market share trends: growing, stable, or contracting relative to competitors - Evaluate product differentiation: coverage breadth, endorsement strategy, claims service reputation - Assess distribution advantage: agency relationships, binding authority, digital channel penetration - Note competitive moats or vulnerabilities (e.g., data advantage in niche lines, adverse selection risk) 5. **Synthesize findings and recommendations** - Rank lines by risk-adjusted return: calendar-year combined ratio, accident-year loss ratio, and reserve adequacy - Flag lines requiring remediation (rate increases, non-renewal actions, coverage restriction) - Identify growth opportunities where rate adequacy exceeds target and competitive position is strong - Quantify reinsurance implications: lines where volatility warrants increased cession or restructured treaties ## Output - **Line Performance Summary Table**: Each line with earned premium, loss ratio (calendar and accident year), expense ratio, combined ratio, rate change trend, and cycle position classification - **Loss Development Exhibit**: Selected ultimate losses by accident year with selected LDFs and methodology notes - **Market Cycle Chart**: Visual overlay of combined ratio and rate changes over time with cycle phase annotations - **Competitive Positioning Matrix**: 2×2 or ranked grid showing relative profitability vs. market share position - **Recommendations**: Prioritized action items per line — grow, maintain, remediate, or exit — with supporting rationale ## Quality Checks - Confirm loss triangles reconcile to financial statement Schedule P or statutory filings [VERIFY: reconciliation targets depend on reporting entity type] - Validate that on-leveling factors correctly reflect cumulative rate changes, not just filed changes - Verify trend selections are supportable: compare selected severity/frequency trends against industry benchmarks and historical fit - Ensure catastrophe vs. attritional loss separation is consistent across all accident years - Cross-check combined ratio components sum correctly (loss ratio + DCCE ratio + expense ratio = combined ratio) - Confirm market benchmark data is from the same reporting period and line definition as the subject portfolio - Flag any line where data credibility is low (fewer than 1,000 claims or 3 development periods) with [VERIFY]
From FDU-INS/Insurance-Skills, Apache-2.0.
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Signals
- Stars
- 80
- Forks
- 18
- Open issues
- 1
- Last commit (this folder)
- May 18, 2026 (5 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- Repository
- github.com/FDU-INS/Insurance-Skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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analyzing-property-casualty-lines skill. Agent Mart. https://agentmart.dev/skills/fdu-ins-analyzing-property-casualty-lines (last updated 2026-10-24)