Probable maximum loss (PML) calculations are performed by several different types of professionals depending on the context. In insurance, underwriters and actuaries handle PML estimates for policy pricing. In commercial real estate, engineering consultants conduct seismic PML assessments during property transactions. And across both industries, catastrophe modeling firms provide the software platforms that power many of these calculations behind the scenes.
Insurance Underwriters and Actuaries
Inside insurance and reinsurance companies, PML estimation falls primarily to commercial underwriters. They use statistical formulas and frequency distribution charts to estimate the highest claim a business is likely to file after a catastrophic event. Insurance companies are responsible for calculating PML across all the policies they underwrite, making it a core part of how they price coverage and manage their exposure to large losses.
PML has deep roots in the underwriting world. A landmark study by the Casualty Actuarial Society collected personal and company definitions of PML from over 100 underwriters and underwriting executives, and found remarkably little agreement on what the term even meant. The study described PML as “one of the most widely used terms in property insurance underwriting” while simultaneously being “one of the least clear concepts in all insurance.” That ambiguity persists today, which is why the specific methodology behind a PML number matters as much as the number itself.
Actuaries also have a significant stake in PML, though their role is more indirect. While underwriters produce the estimates, actuaries analyze the accuracy of those estimates over time and build the mathematical frameworks that underwriters rely on. The feedback loop between the two roles is important: comparing each underwriter’s mean error and variance against company-wide benchmarks helps improve the quality of PML estimates across an organization.
Engineering and Environmental Consultants
In commercial real estate, PML calculations take on a very different form. Here, the question is typically about seismic risk: if an earthquake strikes, what percentage of a building’s replacement value could be lost? These assessments are performed by engineering consulting firms that specialize in property due diligence, not by insurance underwriters.
Firms like Nova Group, GBC employ senior assessors and field assessors who perform PML due diligence assessments following ASTM E2026, the standard guide for seismic risk assessment of buildings. The current version, ASTM E2026-24, was last updated in July 2024 and has gone through multiple revisions since its original release in 1999. These assessments serve commercial real estate lenders, loan servicers, insurers, and equity investors who need to understand a property’s earthquake exposure before completing a transaction.
The professionals doing this work typically have backgrounds in structural engineering, geotechnical engineering, or related fields. They evaluate a building’s construction type, age, soil conditions, proximity to fault lines, and structural features to arrive at a PML figure, usually expressed as a percentage of the building’s value. A PML of 20%, for example, means the assessment estimates the building could lose up to 20% of its replacement cost in a scenario earthquake. Lenders in seismically active regions like California often require these reports before approving commercial mortgages, with thresholds commonly set at 20% to 25% PML.
Catastrophe Modeling Firms
Many PML calculations today rely on sophisticated software rather than manual engineering judgment alone. The catastrophe modeling industry is dominated by a handful of firms that build and maintain the complex simulation platforms used across insurance and real estate.
Verisk is one of the largest providers, offering platforms like Touchstone for direct insurers and Touchstone Re for reinsurance companies modeling complex contract structures. Their tools simulate thousands of potential catastrophe scenarios to estimate loss distributions. Verisk also operates Model Exchange, an open-source platform that gives clients access to over 300 third-party catastrophe models for broader views of risk. Moody’s RMS and CoreLogic are the other major players in this space, each offering their own modeling platforms with different assumptions and methodologies.
The people operating these platforms are typically catastrophe modelers or catastrophe risk analysts, a specialized role that sits at the intersection of data science, actuarial work, and earth science. They configure the models with portfolio data, interpret the outputs, and communicate results to underwriters and executives. At larger insurance and reinsurance companies, entire teams are dedicated to this function. Smaller firms may outsource catastrophe modeling to brokers or consulting firms that run the software on their behalf.
Risk Managers and Corporate Buyers
On the other side of the insurance transaction, corporate risk managers also engage with PML, though they rarely calculate it from scratch. A company’s risk manager uses PML to understand the organization’s worst-case property exposure and to negotiate insurance coverage accordingly. The Casualty Actuarial Society noted that one definition of PML is “pertinent to the insured and his risk manager,” focused on understanding the potential loss to the business, while a separate definition is “more directly pertinent to the underwriter,” tied to underwriting results and pricing.
In practice, risk managers at large corporations often commission PML studies from outside engineering firms or rely on numbers provided by their insurance brokers. They use these figures to decide how much coverage to buy, whether to self-insure a portion of the risk, and how to allocate insurance costs across different properties or business units.
How These Roles Work Together
A single commercial property might have its PML calculated by multiple parties for different purposes. An engineering consultant produces a seismic PML report during the acquisition process so the lender can approve financing. The buyer’s risk manager uses that report to structure their insurance program. The insurance underwriter then calculates their own PML for the policy, possibly using catastrophe modeling software to simulate losses across their entire portfolio including the new property. Each calculation serves a different stakeholder, and the numbers won’t necessarily match because the methodologies and assumptions differ.
This layered process explains why PML remains a somewhat slippery concept despite decades of use. The engineering consultant following ASTM E2026 is answering a different question than the underwriter pricing a policy or the catastrophe modeler running portfolio-level simulations. Understanding who performed a PML calculation, and what standard or methodology they used, is just as important as the number itself.