| name | underwriting-narrative |
| description | Write the underwriting file narrative for a risk: the risk story, exposure quantification, loss-history read, mitigating and aggravating factors, terms and subjectivities rationale, appetite fit, and a refer-or-bind recommendation. Use when asked to write up an underwriting file, document why we're writing a risk, prepare a referral to a senior underwriter, or justify terms and exclusions on a submission. Produces a complete underwriting narrative ready for the file or referral. |
Underwriting Narrative Skill
An underwriting file must let a peer reconstruct why the risk was written, at those terms, at that price โ years later, possibly in front of an auditor or a large loss. This skill writes that narrative: the risk story, the numbers behind it, and the reasoning connecting them to the terms offered.
What This Skill Produces
- A risk story (who the insured is, what they do, why they're buying now)
- Exposure quantification (values at risk, limits deployed, estimated/probable maximum loss)
- A loss-history read distinguishing frequency from severity signals
- Mitigating and aggravating factors, weighed
- Terms rationale โ subjectivities, exclusions, deductibles, each with a reason
- Appetite fit and a refer-or-bind recommendation
Required Inputs
Ask for what's missing; from a thin submission, proceed and mark gaps [information required before bind]:
- The risk โ insured, operations, geography, line of business
- Exposure figures โ sums insured/TIV, revenue, headcount, limits sought
- Loss history โ ideally 5 years, with dates, causes, incurred amounts, open/closed
- Proposed terms โ limit, deductible, premium, exclusions, subjectivities
- Appetite/guidelines context โ target classes, referral thresholds, if available
Narrative Framework
Risk story. Three questions: who is this insured (operations, scale, tenure), what exactly is the exposure (the loss scenarios this line responds to), and why now (new buyer, remarketing, mid-term change)? A remarketed risk needs its reason stated โ price, service, or non-renewal by the incumbent are very different signals.
Exposure quantification. State total values at risk, the limit deployed against them, and an estimated maximum loss with the assumption behind it (e.g. single-site fire, top-location concentration). Limits materially above realistic maximum loss, or below it, both need a sentence.
Loss-history read. Separate the two signals:
- Frequency (many small losses) โ a process/controls problem; responds to deductibles and risk management conditions.
- Severity (rare large losses) โ a volatility/limits problem; responds to price, limit management, and exclusions.
Compute a rough loss ratio against premium if figures allow. Narrate any single loss over ~20% of annual premium individually: cause, fix, recurrence risk. A clean record with low tenure is absence of data, not evidence of quality โ say so.
Mitigating vs aggravating. List both columns honestly. Mitigants must be verifiable (sprinklers confirmed, not "believed"); unverified mitigants become subjectivities.
Terms rationale. Every non-standard term earns its line: each exclusion tied to an exposure you're declining to price; each subjectivity with a deadline and what happens if unmet; deductible tied to the frequency read.
Appetite fit and recommendation. In / edge-of / outside appetite, against which guideline. Recommend bind, bind subject to, refer (naming the referral trigger hit), or decline โ with the one-paragraph reason.
Output Format
Underwriting narrative: [insured / line / inception date]
1. Risk story โ who, what, why now.
2. Exposure โ table: values at risk | limit sought | EML basis | premium.
3. Loss history โ frequency vs severity read, loss ratio, large-loss narratives.
4. Factors โ mitigating | aggravating, two columns, weighed in a closing sentence.
5. Terms & subjectivities โ each with rationale and deadline.
6. Appetite fit โ guideline cited, in/edge/outside.
7. Recommendation โ bind / bind subject to / refer / decline, with reason.
End with: "This narrative is analytical support, not a binding decision. Authority, referral, and bind decisions follow your organisation's underwriting guidelines and applicable regulation."
Quality Checks
Anti-Patterns
