Risk Attribute

Revenue Seasonality

Expert-reviewed Updated: 2026-09-03 Expert-reviewed: 2026-09-04 (Guido Hesse, Hesse Group Holding AG) Version 0.1.0

Revenue seasonality records how evenly the insured's turnover is spread across the year, or whether it is concentrated in specific peak periods, as queried in business interruption proposal forms to correctly time and size the loss of gross profit.

Category
Business interruption/Supply chain
Data type
Enumeration
Risk drivers
Severity, Moral hazard
Underwriting impact
Premium, Condition/Warranty

Typical proposal-form questions

  • Is revenue spread evenly across the year, moderately seasonal, or heavily concentrated in one or a few peak periods?
  • If seasonal, which months or weeks account for the largest share of annual turnover?
  • How would the financial loss differ if a covered event occurred during a peak period rather than during a low-season month?

Evidence

  • Monthly or quarterly revenue breakdown for the past three years
  • Management accounts showing seasonal trading pattern
  • Industry benchmarking data on seasonal demand

Why it matters for underwriting

A business interruption loss is not just a function of how long a disruption lasts, but of when it occurs. For a strongly seasonal business, a loss that falls within the peak trading window can wipe out most of the year’s gross profit even if the interruption itself is short, while the same event in the low season may barely register financially. Underwriters need to understand the seasonal pattern to properly assess the maximum foreseeable loss and to avoid basing pricing on an assumption of even, year-round exposure that does not match the account’s actual trading rhythm.

Capturing the attribute and evidence

Proposal forms ask whether turnover is spread evenly across the year or concentrated in specific peak periods, and, where seasonal, which months or weeks generate the largest share of annual revenue. Underwriters corroborate the declared pattern against a monthly or quarterly revenue breakdown for recent years, management accounts, and, where useful, industry benchmarking data confirming that the claimed seasonality is consistent with the sector norm.

Effect on coverage, premium and conditions

Businesses with a well-documented, evenly spread revenue pattern are more straightforward to price using average monthly exposure. Strongly seasonal businesses require the maximum foreseeable loss to be assessed against peak-period exposure rather than an annual average, which can increase the rate relative to a superficially similar non-seasonal account, and may prompt a condition requiring risk improvement measures to be in place and verified before the peak season begins.

Mitigation measures

Recommended measures include timing planned maintenance, testing and risk improvement works outside the peak trading window, building contingency capacity or alternative sourcing specifically to protect peak-season output, and reviewing the declared seasonal pattern periodically as the business mix or sales channels evolve.

Standards and codes

  • ISO 31000:2018 – Risk management, Guidelines