Insurance renewal or D&O review
Produce a defensible cross-portfolio exposure number instead of a manually reconciled estimate.
— Risk & Compliance
Cross-portfolio liability cap aggregation
Reads every liability cap in a contract portfolio, derives actual exposure as a number, and aggregates it by entity, flagging uncapped contracts separately.
- Risk & Compliance
- Traceable reasoning
- Runs anywhere
2–3 weeks → ~25 minutes
For a full population, not a sample
No coding required
- Input
- A contract register with counterparty, entity and annual fee columns
- Output
- An exposure heatmap aggregated by entity
- Runs in
- Skillsize · ChatGPT · Claude · Copilot
- Export
- SKILL.md · MCP
- Time saved
- ~2–3 weeks per run
— USE CASES
What people use Cross-portfolio liability cap aggregation for
M&A due diligence
Identify which contracts carry disproportionate uncapped or high-cap liability before valuation assumptions are finalised.
Vendor and customer concentration
Spot the ten contracts contributing the most exposure so negotiation priority is data-driven.
What it works from
- A contract register with counterparty, entity and annual fee columns
- The contract files or extracted cap clauses
- Your cap-basis conventions and any carve-outs to treat as uncapped
What you get back
- An exposure heatmap aggregated by entity
- A separate total for uncapped contracts
- The top ten contracts by disproportionate liability risk
— HOW IT BEHAVES
How Cross-portfolio liability cap aggregation produces its result
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
Row-level table processing
Every row of your table is processed on the same basis, however long the table is.
Charted, not just stated
The pattern is visualised from the computed data, so the trend is legible at a glance.
Composed as work product
Findings are written up as a document that reads like professional output rather than raw model text.
Enriched row by row
Each row gains derived columns from the analysis, keeping the source data and the judgement side by side.
Roll-up alongside detail
Detail rows are summarised into the grouped view without losing the underlying lines.
Why this is expensive by hand
The number insurers and finance ask for — total liability exposure across the portfolio — is usually buried in contracts with caps expressed as multiples, fixed sums or uncapped carve-outs. Insurance renewal or D&O review is the typical trigger — produce a defensible cross-portfolio exposure number instead of a manually reconciled estimate. Done properly it is defensible; done at pace it becomes a judgement call nobody can retrace. And "properly" usually means 2–3 weeks of manual work.
How this Skill produces it
Here the same job runs as a Skill. Your material goes in; an exposure heatmap aggregated by entity comes out, alongside a separate total for uncapped contracts. The judgement is built in — how items are broken up, what standard they are held to, and where the run stops for a human review. The practical effect: 2–3 weeks of manual work becomes a ~25 minutes run, held to an identical standard on the tenth engagement as on the first.
Who it's for
- Independent consultants codifying their own methodology
- Strategy and transformation teams standardising delivery
- Internal advisory functions under pressure to produce faster
- Operators who need defensible output, not a one-off chat answer
Run it in Skillsize — or export it anywhere
Cross-portfolio liability cap aggregation exports as a structured SKILL.md file and is MCP-ready, so the same method runs in ChatGPT, Claude, Copilot or your own AI products. Adapt it to your methodology, and the intelligence stays yours — not locked to one vendor.
ChatGPTClaudeCopilotAI Products (MCP)
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