Business interruption (BI) losses in the hospitality sector present unique challenges for insurers, particularly where headline indicators such as reduced capacity or falling occupancy can obscure the true economic impact of an incident. Hotels operate across multiple revenue streams—rooms, food and beverage, events, and ancillary services—while demand is influenced by seasonality, customer mix, and external market factors.
Assessing loss in this environment requires more than applying standard BI methodologies. It calls for a detailed understanding of how hotels actually generate revenue, how they respond operationally to disruption, and how these realities align with policy wording, indemnity principles, and evidential standards typically applied by insurers and reinsurers.
Understanding revenue loss: demand, segmentation and real trading conditions
At the centre of most hotel BI claims is the question of lost room revenues. While this is typically driven by occupancy and average daily rate (ADR), these metrics alone rarely tell the full story.
In one case, a resort was forced to close a number of villas following an incident. On the surface, reduced room inventory pointed to an inevitable loss. However, analysis of actual occupancy levels during the indemnity period showed that the remaining undamaged villas were sufficient to meet demand. In effect, no room revenue was lost, as the counterfactual ‘but-for’ analysis showed that demand during the indemnity period would not have exceeded the available room inventory. Reduced capacity alone was therefore insufficient to establish indemnifiable loss.
By contrast, larger hotels introduce a different level of complexity. A major city hotel with over 1,800 rooms required a more granular approach, with performance driven by a diverse customer mix of corporate, group, transient, and airline crew bookings. Applying a simple average occupancy and ADR would have produced a misleading result, masking rate volatility and demand concentration by segment. Instead, expected performance was reconstructed by segment and room type, with historical booking curves and contracted rates tested against known demand drivers during the indemnity period.
In addition, external demand drivers—such as major trade shows and events—played a significant role in shaping expected occupancy. Accurately assessing the loss required aligning historical performance with these forward-looking indicators to reflect how the hotel would reasonably have traded during the indemnity period. Assumptions were tested not only for plausibility but also for materiality, with particular focus on avoiding upward bias in projected rates or occupancy during peak periods.
This illustrates a critical BI principle: the loss must be assessed against the counterfactual ‘but-for’ position, rather than assumed capacity constraints. Reduced physical availability does not, of itself, establish loss unless it can be shown that demand would have materialised.
Mitigation, displacement and the limits of policy response
Operational responses following an incident can further complicate BI assessments. One common practice is the relocation, or “walking”, of guests to alternative properties.
Where guests are moved within the same hotel group, revenue may effectively be retained within insured entities and may not constitute a recoverable loss. However, when guests are relocated to third-party hotels, the position changes. The insured may lose room revenue while also incurring additional costs where competitor rates exceed original bookings. These costs are typically uneconomic and may only be recoverable under Additional Increase in Cost of Working (AICW) extensions.
Hotels may also offer discounts or waive charges entirely as a goodwill measure to protect brand reputation. While commercially understandable, these actions introduce further complexity. Discounts often translate to a direct loss of profit, while full waivers may result in both lost profit and unrecovered costs. From a policy perspective, these costs must also satisfy tests of necessity and causation. Commercially rational actions taken to protect brand reputation do not automatically translate into indemnifiable loss, particularly where they extend beyond what was strictly required to mitigate insured damage.
These scenarios highlight the importance of distinguishing between revenue that is genuinely lost, revenue that is displaced, and costs that fall within (or outside) the scope of cover.
A disciplined approach to complex hospitality BI claims
In hotel BI claims, minor movements in assumed mix or peak-period rate can have a disproportionate impact on gross profit. Sensitivity testing around these assumptions is therefore critical in distinguishing genuine loss from modelling artefact.
Rather than relying on formulaic applications of occupancy and ADR, this disciplined approach focuses on how the hotel would have traded in practice had the insured event not occurred, tested against both operational behaviour and policy intent.
This approach underpins McLarens’ work in the hospitality sector, supporting insurers with independent, evidence-based assessments that align operational reality with policy intent in complex business interruption claims.
