The industry trend toward single, large-capacity processing units — oversized SAG mills, high-throughput crushers — was designed to extract economies of scale
The Number That Leads
Between 2006 and 2025, Marsh analyzed significant insured loss events across the global mining sector and found that business interruption accounts for approximately 80% of total gross losses. Total recorded losses in the dataset reached $15.3 billion, placing the BI component at roughly $12 billion. Physical damage — the destroyed equipment, the collapsed structure — is the trigger. Lost production is the cost.
That headline figure gains weight when set against the operational failure categories driving it. Fires, explosions, machinery breakdowns, and geotechnical failures together represent approximately 70% of gross claim value, or around $10.3 billion. Fire and explosion events alone account for nearly one-third of all claims, with an average loss size of $115 million per event. These are not tail-risk outliers. They are the routine loss landscape.
What Sits Behind the Number
Three structural features explain why BI costs dominate physical damage in mining more than in other industrial sectors.
The first is equipment architecture. The industry trend toward single, large-capacity processing units — oversized SAG mills, high-throughput crushers — was designed to extract economies of scale. It also eliminated redundancy. Patrick Walker, global head of group risk finance at Rio Tinto, noted in the Marsh report that dependence on complex, interconnected equipment amplifies single-point failures. James Fryer of the Mining Insurance & Risk Association put it plainly: when one mill fails, there is no fallback, and multi-month production outages follow from a single mechanical event.
The second is parts availability. Critical components for large mills, crushers, and conveyors are not warehoused at scale. The Marsh report cites cases where the absence of a spare mill motor forced an operation to wait more than a year for a replacement. That extended timeline translates directly into extended revenue loss — far beyond what policy sub-limits typically cover.
The third is commodity price exposure. Lars Gono, Swiss Re’s global head of mining, observed a substantial increase in the BI component of claims, partly driven by commodity price volatility. When a loss event coincides with elevated metal prices, every lost tonne of production carries disproportionately higher revenue impact even when physical damage is contained. A fire that would have produced a $40 million claim at trough pricing may generate a $90 million claim at cycle peak. The damage is identical; the production value is not.
Geotechnical and structural failures sit at the catastrophic end of this spectrum. Though less frequent than mechanical failures, they produce the largest individual losses in the dataset. The 2019 Brumadinho dam disaster in Brazil resulted in a settlement exceeding $7 billion with Brazilian authorities. The Fundão dam collapse in 2015 preceded it with comparable severity. These events are outliers in frequency but not in probability — and their BI tail, tied to site-wide shutdowns, regulatory intervention, and remediation timelines, extends well beyond the physical event itself.
What This Is Worth in Your Operation
The recovery gap is where the financial exposure becomes concrete. Mining companies recover approximately 45–55% of their losses through insurance — a range that has held consistently across the dataset period. Sectors with more standardized risk profiles, such as renewable energy, report recovery ratios near 75%. That 20–30 percentage-point gap represents a structural difference in how much operational loss mining absorbs on its own balance sheet.
The gap has identifiable causes. Most mining policies include waiting periods — often several weeks — before business interruption coverage begins. By the time coverage activates, a significant portion of early-stage revenue loss has already been absorbed. Sub-limits then cap indemnity for specific hazard categories: natural catastrophes, tailings events, underground operations. Machinery breakdown claims carry some of the lowest recovery ratios in the dataset, below 50% on $1.6 billion in gross recorded losses — sitting at the intersection of high frequency, long parts lead times, and constrained policy design.
Flooding compounds the natural catastrophe exposure. Within the nat cat loss category, flooding drives nearly 70% of gross claim value. That proportion is expected to grow as climate-driven rainfall intensity increases across mining jurisdictions. Drainage infrastructure and flood scenario planning are no longer optional resilience measures — they are operating cost decisions with an insurance leverage effect attached.
What the Data Does Not Say
This dataset captures insured losses only, which means uninsured events, near-misses, and incidents below reporting thresholds are absent. The analysis reflects what was claimed, not the full population of operational disruptions. Operations with lower insurance penetration — common in some jurisdictions — are structurally underrepresented.
The dataset also cannot confirm whether the trend toward larger processing units has accelerated since 2020, or whether the BI share of losses is still rising or has plateaued. Gono’s observation about a substantial increase in the BI component is directional, not precisely quantified across time periods. The commodity price amplification effect is real but variable — it depends on where in the cycle a loss event occurs, which is not predictable in advance.
Finally, the Marsh report’s recommendations around captives, parametric solutions, and enhanced program design represent options rather than proven remedies. Their effectiveness in closing the recovery gap depends on negotiated terms, specific site risk profiles, and insurer appetite — none of which are uniform across the industry.
The Implementation Question
Before your next policy renewal, one question is worth putting directly to your risk and insurance team: for each of your major processing assets, what is the current waiting period before BI coverage activates, what are the sub-limits on machinery breakdown and geotechnical events, and does your critical spare parts program actually reduce the exposure window those sub-limits were designed to cover?
The data shows the problem is structural, not incidental. The question is whether the gap between what you lose and what you recover is being managed with the same discipline as your maintenance schedule — or whether it is simply being absorbed.
Sources
- Riskandinsurance — Business Interruption Drives 80% of Mining Losses as Industry Faces Volatile, Under-Recovered Claims (Link)
