Review the evidence signals before interviewing. Then use the anchored descriptions—not instinct alone—to choose the score that best matches each answer.
01
Evaluation factor
Technical command
35% weight
Check fluency with catastrophe models (RMS, Verisk/AIR, Oasis LMF), CMIP6 downscaling, RCP/SSP pathways, exceedance probability curves, and how they adjust vendor event sets for climate signal.
Evidence to listen for
Commands the instruments, models, or reporting standards the role turns on
Can build the analysis rather than only interpret someone else's
Knows the assumptions inside a model and which ones actually drive the answer
Fluent in the frameworks and disclosure regimes that apply
Five-point scoring guide
1
Poor
Cannot explain the instruments or standards they claim to work with.
2
Needs Improvement
Interprets others' analysis but cannot build or defend it.
3
Satisfactory
Solid working command; thin on unfamiliar structures or standards.
4
Very Good
Builds the analysis and knows which assumptions actually move the answer.
5
Excellent
Names specific model versions and perils, explains secondary uncertainty and demand surge handling, and where vendor views understate flood or wildfire.
02
Evaluation factor
Deals and deliverables that closed
25% weight
Probe deliverables that shipped: repriced wildfire or coastal flood portfolios, ORSA climate scenario chapters, TCFD or ISSB disclosures, reinsurance submissions, or Solvency II internal model change files.
Evidence to listen for
Names transactions, filings, or reports they worked, with size, counterparties, and their own scope
Distinguishes their contribution from the deal team's
Knows what happened afterwards, including what underperformed
Can describe one that fell over and why
Five-point scoring guide
1
Poor
No completed work; describes process rather than outcomes.
2
Needs Improvement
Involved in transactions but cannot state their own scope.
3
Satisfactory
Real deliverables with adequate ownership; outcomes described loosely.
4
Very Good
Named transactions or filings with clear personal scope and honest post-mortems.
5
Excellent
Cites named portfolios with premium, exposure or loss ratio movement, and the regulator, reinsurer or board that accepted the work.
03
Evaluation factor
Risk judgement
25% weight
Test how they set risk appetite where data is thin: unmodelled perils, accumulation limits by CRESTA zone, attachment point choices, and refusing or surcharging exposures under political pressure.
Evidence to listen for
Distinguishes a modelled risk from a real one
States confidence and what would change their view
Comfortable disagreeing with a number that suits everybody
Knows the limits of the data behind a projection, especially over long horizons
Five-point scoring guide
1
Poor
Treats model output as truth; no sense of data limits.
2
Needs Improvement
Reports numbers without qualifying them; avoids unwelcome conclusions.
3
Satisfactory
Reasonable judgement; qualifies findings when prompted.
4
Very Good
States confidence unprompted and will hold an unpopular position on evidence.
5
Excellent
Distinguishes model uncertainty from genuine trend, states thresholds triggering withdrawal or subsidised cover, and owns a call that proved wrong.
04
Evaluation factor
Explaining it to decision-makers
15% weight
Assess how they brief underwriters, actuaries and boards: translating return periods and average annual loss into pricing and capital decisions without hiding tail assumptions.
Evidence to listen for
Explains a technical position to an investment committee, board, or regulator so they can act on it
Writes to the standard the audience is held to
Handles challenge without either caving or digging in
Works across legal, operations, and external counterparties
Five-point scoring guide
1
Poor
Cannot communicate beyond technical peers.
2
Needs Improvement
Explanations lose the audience or oversimplify to the point of error.
3
Satisfactory
Adequate with familiar audiences; less effective under challenge.
4
Very Good
Explains clearly to committees and regulators and holds up under challenge.
5
Excellent
Turns EP curves into concrete underwriting guidance, surfaces key assumptions plainly, and has changed an executive decision with a single clear exhibit.
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