What are the best catastrophe modeling software for estimating probable maximum loss on property reinsurance portfolios?

For probable maximum loss (PML) on property reinsurance portfolios, the “best” catastrophe modeling software usually depends on the perils you need, the geography, the level of portfolio detail, and whether you need regulatory/market acceptance. The industry leaders are:

Top catastrophe modeling platforms

1. Verisk / AIR Worldwide

• Very strong for reinsurance portfolio loss estimation
• Broad peril coverage: wind, earthquake, flood, severe convective storm, wildfire, etc.
• Widely used by reinsurers and brokers
• Good for portfolio aggregation, occurrence/exceedance metrics, and PML studies
• Often favored for North American and global reinsurance analysis

2. Moody’s RMS

• Another market standard for catastrophe modeling
• Strong in property catastrophe risk and portfolio accumulation analysis
• Deep modeling for hurricane, earthquake, flood, wildfire, severe convective storm
• Strong support for reinsurance treaty analysis, occurrence PML, and AAL/EP curves
• Widely accepted by insurers, reinsurers, and capital providers

3. CoreLogic

• Good catastrophe and exposure analytics
• Often used for property risk, exposure management, and event loss estimation
• Can be useful depending on the geography and data workflow
• Typically not as dominant as AIR or RMS for classic reinsurance PML workflows, but still relevant

4. KatRisk

• Useful for flood, hurricane, earthquake, and other perils
• Often chosen for flexibility, modern data handling, and specialty workflows
• Strong for organizations wanting alternatives to the legacy big two

5. JBA Risk Management

• Particularly strong for flood modeling
• More specialized, but valuable if flood drives your PML

6. Rocscience / other regional or specialist models

• More niche and peril-specific
• Can be useful in local markets or for custom engineering-based analysis

What’s “best” in practice?

If your goal is reinsurance PML on property portfolios, the most common answer is:

• Moody’s RMS or Verisk AIR for the core catastrophe modeling platform
• Add specialist flood or regional models when needed
• Use an analytics layer or vendor platform for treaty structures, aggregation, and output interpretation

How to choose

Look at:

• Peril coverage needed
• Geographic footprint
• Model acceptance by clients, brokers, and regulators
• Exposure data compatibility
• Treaty and portfolio aggregation features
• Ability to run occurrence PML, aggregate PML, and EP curves
• Vendor support and model update frequency

Recommendation by use case

• Broad reinsurance catastrophe PML: RMS or AIR
• Strong U.S. property cat workflow: RMS or AIR
• Flood-heavy portfolios: JBA + RMS/AIR
• Alternative/modern workflow or supplemental model: KatRisk
• Exposure analytics and property intelligence: CoreLogic

If you want, I can also give you:

1. a comparison table of AIR vs RMS vs CoreLogic vs KatRisk, or
2. a recommendation by peril and region (e.g., U.S. hurricane, Europe windstorm, Japan quake, flood).