Walk me through how you evaluate a new risk submission.

I start by reviewing the submission information for completeness. Missing or inconsistent data is itself a signal. Then I assess the risk against our appetite: does this class of business, geography, and limit structure fall within what we write? If it does, I work through the exposure: what are the key drivers of loss for this type of risk, what is the historical loss experience, and how does this account compare to our book? I use our rating models as a starting point but I treat them as tools, not conclusions. For anything materially different from our standard risk profile I will ask additional questions or request a survey. I then price based on expected loss, loading for expenses and profit margin, and benchmarking against the market rate. If the broker has submitted a target premium that differs significantly from my assessment, I will either negotiate or decline with a clear explanation.

How do you balance underwriting discipline with commercial pressure to grow the book?

I treat underwriting discipline and book growth as compatible when the pricing is right and the risk quality meets appetite. The conflict arises when brokers push for a premium below what the risk warrants, and the commercial pressure is to accept anyway to maintain the relationship or hit volume targets. My approach is to be transparent about my pricing rationale, explain clearly why a given risk is priced as it is, and look for a middle ground through risk improvement or coverage adjustment where that is possible. What I will not do is write a risk at a rate that I know will not cover expected loss over time. Short-term relationship damage from a firm decline is recoverable. Underwriting a poor book is not. I also track how declined risks perform so I have data to support my decisions.

How do you approach pricing a risk when the market is highly competitive?

I start from my own loss cost estimate and work upward, not from the market rate downward. If the market is pricing below what I believe the risk warrants, I need to understand why before I follow suit: are competitors seeing something I am not, or are they under-pricing for market share? I will use market intelligence and loss data to test my assumptions. If my analysis still shows the market rate is inadequate, I will offer terms at my minimum acceptable rate and accept that some business will go elsewhere. Chasing market price in a soft market is how underwriters build books that haemorrhage at the next major loss event. I would rather write less business at adequate rates than more business that is mispriced.

How do you use data and analytics in your underwriting decisions?

I use both internal and external data. Internally, I look at loss ratios by class, territory, and account size to understand where our book is performing and where it is deteriorating. Externally, I use industry loss data, third-party risk scoring tools, and sector reports to benchmark my pricing and spot emerging risks. For larger commercial accounts I also use exposure data: property values, revenue figures, headcount, and operational details that feed into my rating model. I treat models as structured guidance rather than answers, particularly for complex or novel risks where the data is sparse. The analytical tools help me be consistent across a high volume of decisions, but the judgment on edge cases still has to come from underwriting experience.

Tell me about a risk you declined that you were under pressure to accept.

A major broker submitted a large property risk in a flood-prone area with a loss history that showed three significant events in five years. The broker argued the client had invested in flood mitigation and the premium should reflect the improvements. I reviewed the survey report and found that the mitigation measures reduced but did not eliminate the exposure, and that the post-mitigation risk was still priced below what our models required. The broker pushed hard, citing the relationship and the size of the premium. I offered terms at a rate that reflected the residual exposure with a clause requiring annual survey updates. The broker placed it elsewhere. That account suffered a further flood loss eighteen months later. The discipline to decline was the right call.

Describe a time your underwriting decision turned out to be wrong. What did you learn?

I wrote a professional indemnity account for a technology consultancy at a rate I believed was adequate based on their stated revenue and claims history. A year into the policy they had a significant claim that revealed the actual scope of their work was considerably broader than the submission had described. The claim was covered, but the rate was not appropriate for the actual risk. From that experience I strengthened my approach to professional indemnity submissions: I now require a sample of recent contracts and client descriptions rather than relying on the broad activity classification on the submission form. Better questions at the point of underwriting prevent expensive surprises at the point of claims.

Tell me about a time you had to make a decision with incomplete information.

I received a submission for a mid-size construction liability risk with a loss run that was missing two years of data. The broker explained the client had changed brokers during that period and the records were difficult to obtain. Rather than waiting indefinitely or declining outright, I asked for the client's own incident reports for the missing period and a senior management reference on their safety culture. Those two sources gave me enough directional information to assess the risk with a higher confidence load built into the pricing to account for the data gap. I wrote the account at a rate that reflected the uncertainty, and when the missing information arrived later it confirmed my assessment was appropriately conservative.

How do you calculate a burning cost and when do you use it?

Burning cost is the ratio of incurred losses to earned premium over a historical period, adjusted for trend and development. It gives you a pure loss cost before expenses and profit loading. I use it primarily for accounts with credible loss history, typically three to five years of data with enough premium volume to make the ratios statistically meaningful. I adjust for trend by indexing historical losses to current cost levels, for development by using loss development factors to project incurred losses to ultimate, and for exposure changes such as revenue growth or operational shifts. Where the history is sparse or the account is too small to be statistically credible, I rely more heavily on manual rating and market benchmarks.

What is your approach to setting deductibles and policy limits?

Deductibles serve two purposes: they reduce moral hazard by keeping the insured financially involved in small losses, and they reduce premium for risks where the insured has a high frequency of attritional losses they can absorb. I recommend a deductible level that is meaningful relative to the insured's financial position but not so high that a routine loss creates a cash flow problem. For limits, I start with the insured's maximum probable loss in a realistic adverse scenario, cross-reference with any contractual requirements they face, and then assess whether the premium for that limit is proportionate to the actual probability of reaching it. I use reinsurance or co-insurance to manage my net exposure where the gross limit is large.

How do you assess the impact of emerging risks such as cyber or climate change on your book?

I treat emerging risks as requiring more frequent and more humble reassessment than established classes. For cyber, the loss environment changes faster than historical data can reflect, so I weight recent large-loss events and industry threat intelligence more heavily than multi-year averages. I also review policy wording carefully for silent cyber exposure in liability and property lines. For climate risk, I use catastrophe modelling outputs as a starting point but overlay my own judgment on how modelled loss projections translate to specific geographies in my book. Both risk types require accepting that models carry more uncertainty than usual, which should translate into higher confidence loads in pricing.

Underwriter

Underwriter interviews test both your analytical ability and your judgment, and the judgment piece is often harder to demonstrate. Pricing risk correctly is table stakes; the harder skill is knowing when to decline a risk even under commercial pressure, and being able to explain that decision clearly to a broker who won't like the answer. This guide covers the questions that come up most often and what strong answers tend to look like.

For general interview preparation tips, read our guide to common interview questions.

Prepare further

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What Hiring Managers Look for in Underwriter Interviews

What hiring managers really look for in Underwriter candidates:

Structured analytical thinking, not just experience pattern-matching. Interviewers want to see how you work through a risk you haven't seen before, not just how quickly you can match it to something familiar.
Pricing discipline that includes knowing when to walk away. Candidates who can explain why they declined a risk, and what would have had to change for them to write it, are more useful than those who only talk about what they've written.
Market awareness at the book level. Knowing where your portfolio sits relative to market rates, and what the implications are for profitability over time, is the kind of thinking that separates technical underwriters from commercial ones.
Claims literacy. Underwriters who understand how claims actually develop and settle make better pricing decisions, because they're not treating loss as an abstract number on a model.
Clear communication with brokers, including on declines. Explaining a decline in a way that preserves the relationship and gives the broker something useful to work with is a skill that most interviewers will probe for directly.

Questions to Ask Your Interviewer

→What classes of business does the team primarily underwrite, and what is the appetite for growth in each?
→How is the underwriting authority structured, and what level of referral would this role require?
→How does the team approach emerging risks like cyber and climate exposure?
→What is the current state of the book in terms of loss ratio and how has performance trended over the last three years?
→What systems and data tools does the underwriting team use for pricing and portfolio management?

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