analyzing-cyber-insurance
Structures cyber insurance evaluation with coverage assessment, limit adequacy, and claims scenario analysis.
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.
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About
Use cases: testing
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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codeload.github.com· found in install command
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~/.claude/skills/analyzing-cyber-insurance
What's inside
- Skill name
analyzing-cyber-insurance- Description
- Structures cyber insurance evaluation with coverage assessment, limit adequacy, and claims scenario analysis. Use when evaluating cyber coverage, analyzing policy terms, or assessing cyber insurance adequacy.
- License
- Apache-2.0
- Metadata
- author: casemark
- Instructions
- 78 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Analyzing Cyber Insurance
## When To Use
- Evaluating a new or renewal cyber insurance policy for coverage adequacy
- Comparing competing cyber policy quotes across carriers
- Assessing whether existing cyber limits align with the insured's risk profile
- Running claims scenarios to stress-test policy response under breach events
- Reviewing policy language for sublimit traps, retroactive date gaps, or exclusion pitfalls
- Advising on tower structure or excess placement for large cyber programs
## Inputs To Gather
- **Policy documents**: Full policy form including declarations page, endorsements, and any manuscript amendments
- **Insured profile**: Industry vertical, annual revenue, record count (PII/PHI/PCI), geographic footprint, and IT infrastructure summary
- **Loss history**: Prior cyber claims, near-misses, and any regulatory actions or litigation
- **Risk assessment data**: Most recent penetration test results, SOC 2 or ISO 27001 status, incident response plan maturity
- **Program structure**: Primary and excess layers, attachment points, carrier line-up, and any shared/quota arrangements
- **Benchmark data**: Peer company limits, industry loss trends (e.g., Advisen, NetDiligence claims studies), and broker market intelligence
- **Coverage requirements**: Contractual insurance obligations, regulatory mandates, and board risk appetite statements
## Workflow
1. **Map coverage grants against risk exposures**
- Parse insuring agreements for first-party (business interruption, data restoration, extortion, forensic costs, notification/credit monitoring, crisis management/PR) and third-party (network security liability, privacy liability, regulatory defense and penalties, media liability, PCI-DSS fines) coverages
- Flag any coverage grants that are absent given the insured's exposure profile
- Note whether coverage triggers are occurrence-based, claims-made, or claims-made-and-reported, and confirm retroactive date adequacy
2. **Analyze key policy terms and conditions**
- Identify sublimits that effectively cap high-frequency loss categories (e.g., ransomware/extortion sublimit, dependent business interruption sublimit, voluntary notification sublimit)
- Review waiting period / hours clause for business interruption — compare against insured's actual RTO expectations
- Examine consent requirements for breach counsel, forensic vendors, and ransom payments [VERIFY carrier panel requirements]
- Assess war/terrorism and nation-state exclusions — note whether carve-backs for cyberterrorism exist
- Review infrastructure/cloud exclusion wording — confirm coverage extends to hosted environments (AWS, Azure, SaaS dependencies)
- Check prior acts, pending/prior litigation, and prior knowledge exclusions for gaps
3. **Evaluate limit adequacy**
- Model loss scenarios across severity tiers:
- **Low**: Single employee credential compromise, limited data exposure (~5K records)
- **Medium**: Ransomware event with 72-hour operational downtime, partial data exfiltration (~500K records)
- **High**: Systemic breach with regulatory investigation across multiple jurisdictions, class action exposure (~5M+ records)
- For each scenario, stack estimated costs: forensic investigation, notification, credit monitoring, legal defense, regulatory fines, business interruption loss, and reputational/crisis management spend
- Compare modeled losses against aggregate and per-occurrence limits, noting erosion risk from sublimited coverages
- Benchmark limits against industry peers by revenue band and data volume [VERIFY current benchmark sources]
4. **Assess program structure and pricing**
- If tower program: evaluate attachment points, follow-form consistency across excess layers, and any differences in conditions (DIC) or differences in limits (DIL) issues
- Flag anti-stacking provisions, batch/related-claims clauses, and interrelated wrongful acts definitions that could consolidate multiple events into a single limit
- Compare premium-per-million across layers and against market benchmarks
- Identify retention (SIR/deductible) appropriateness relative to the insured's balance sheet and incident frequency
5. **Review exclusions and conditions for coverage disputes risk**
- Catalog exclusions most likely to generate coverage disputes: failure to maintain minimum security standards, criminal/fraudulent acts, contractual liability, bodily injury/property damage, unencrypted device exclusions
- Assess notice/reporting requirements — identify strict compliance conditions that could void coverage
- Note any cooperation and subrogation obligations that impose operational burdens during active incidents
## Output
Structure the analysis report with the following sections:
- **Executive Summary**: One-page overview of coverage adequacy rating (Strong / Adequate / Gaps Identified / Inadequate), top three findings, and priority recommendations
- **Coverage Matrix**: Table mapping each insuring agreement to the insured's risk exposures, noting sublimits, retentions, and waiting periods per coverage part
- **Limit Adequacy Analysis**: Scenario-based loss modeling results with comparison to purchased limits and benchmark data
- **Terms and Conditions Review**: Annotated list of policy provisions with risk ratings (Green / Yellow / Red) based on potential to restrict or deny coverage
- **Exclusion Risk Assessment**: Ranked list of exclusions by likelihood and severity of coverage dispute
- **Program Structure Evaluation**: Visual or tabular representation of tower structure with commentary on layering efficiency and pricing
- **Recommendations**: Prioritized action items — coverage enhancements to negotiate, limit increases to pursue, endorsements to request, and alternative market options
## Quality Checks
- Every sublimit, retention, and waiting period from the declarations page is accounted for in the coverage matrix
- Loss scenarios use defensible cost assumptions with sources cited (NetDiligence, Ponemon/IBM, Verizon DBIR) [VERIFY latest study year and figures]
- Exclusion analysis references specific policy section numbers and endorsement form numbers
- Retroactive date, extended reporting period (tail), and policy period are confirmed and noted
- All jurisdictional regulatory exposure is identified — GDPR, CCPA/CPRA, HIPAA, state breach notification statutes as applicable [VERIFY relevant jurisdictions for insured's footprint]
- Recommendations distinguish between items achievable in current negotiation vs. next renewal cycle
- Report flags any areas where actuarial loss modeling or independent broker review is warranted beyond the scope of this analysisFrom 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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Cite this page
analyzing-cyber-insurance skill. Agent Mart. https://agentmart.dev/skills/fdu-ins-analyzing-cyber-insurance (last updated 2026-10-24)