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Science ResearchTop 8 Best Catastrophe Modeling Software of 2026
Compare the top Catastrophe Modeling Software tools with a top 10 ranking for insurers and risk teams. Explore picks now.
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
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Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Verisk
Integrated catastrophe model workflow for hazard, exposure, and scenario-based risk quantification
Built for insurance and reinsurance teams needing enterprise catastrophe modeling and scenario analysis.
OpenQuake Engine
Logic-tree probabilistic hazard engine with ground-motion model selection and disaggregation
Built for teams running reproducible earthquake hazard studies with engineering-grade control.
HAZUS
Integrated FEMA HAZUS loss estimation linking hazard intensity to exposure damage and losses
Built for agencies needing standardized FEMA catastrophe modeling with GIS-ready outputs.
Related reading
Comparison Table
This comparison table organizes catastrophe modeling software used for seismic, hurricane, flood, and multi-hazard risk analysis across key capabilities like hazard modeling workflows, input data support, and output formats. Readers can compare open-source toolchains such as OpenQuake Engine and OpenSHA against commonly used frameworks such as Verisk and HAZUS, plus add-on response tooling like HURREVAC. The table highlights how each tool handles scenario setup, ground-shaking or impact computation, and integration into risk and decision pipelines.
| # | Tool | Category | Overall | Features | Ease of Use | Value |
|---|---|---|---|---|---|---|
| 1 | Verisk Supports catastrophe modeling workflows for insurers and reinsurers with hazard and vulnerability modeling, exposure processing, and loss analytics. | cat modeling suite | 8.5/10 | 9.0/10 | 7.8/10 | 8.6/10 |
| 2 | OpenQuake Engine Runs open source hazard and risk calculations for earthquakes with hazard assessment modules and loss estimation pipelines. | open source engine | 8.2/10 | 8.9/10 | 7.6/10 | 7.9/10 |
| 3 | HAZUS Provides loss estimation and scenario tools for hazards using FEMA methodologies for earthquake, hurricane, and flood damage modeling. | scenario modeling | 8.1/10 | 8.7/10 | 7.6/10 | 7.9/10 |
| 4 | Quantitative Seismic Hazard Analysis Toolkit (OpenSHA) Supports seismic hazard and risk calculations through an open source framework for executing model logic trees and hazard calculations. | seismic hazard | 8.1/10 | 8.7/10 | 7.4/10 | 7.9/10 |
| 5 | HURREVAC Models hurricane wind and related hazards for hazard assessment with parameterized hurricane track and intensity inputs. | hurricane hazard | 7.2/10 | 7.4/10 | 7.1/10 | 7.0/10 |
| 6 | Fathom Computational Framework Provides a computational environment for quantitative risk analytics and hazard modeling workflows used in research and decision support. | research analytics | 7.2/10 | 7.8/10 | 6.6/10 | 7.0/10 |
| 7 | EMDAT Supplies disaster event data and tools that support catastrophe modeling research through standardized disaster occurrence records. | disaster database | 7.2/10 | 7.4/10 | 6.9/10 | 7.3/10 |
| 8 | AEL Provides specialized catastrophe modeling software and services for risk analytics used in insurance and research workflows. | cat modeling | 7.2/10 | 7.4/10 | 6.8/10 | 7.4/10 |
Supports catastrophe modeling workflows for insurers and reinsurers with hazard and vulnerability modeling, exposure processing, and loss analytics.
Runs open source hazard and risk calculations for earthquakes with hazard assessment modules and loss estimation pipelines.
Provides loss estimation and scenario tools for hazards using FEMA methodologies for earthquake, hurricane, and flood damage modeling.
Supports seismic hazard and risk calculations through an open source framework for executing model logic trees and hazard calculations.
Models hurricane wind and related hazards for hazard assessment with parameterized hurricane track and intensity inputs.
Provides a computational environment for quantitative risk analytics and hazard modeling workflows used in research and decision support.
Supplies disaster event data and tools that support catastrophe modeling research through standardized disaster occurrence records.
Provides specialized catastrophe modeling software and services for risk analytics used in insurance and research workflows.
Verisk
cat modeling suiteSupports catastrophe modeling workflows for insurers and reinsurers with hazard and vulnerability modeling, exposure processing, and loss analytics.
Integrated catastrophe model workflow for hazard, exposure, and scenario-based risk quantification
Verisk stands out for catastrophe modeling tied to an enterprise-grade data and analytics ecosystem across insurance, risk, and resilience use cases. Core capabilities center on hazard modeling, risk quantification, and scenario analysis used for underwriting support and portfolio exposure planning. The platform’s strength is its integration of specialized catastrophe peril science and model workflows into decisioning processes for risk teams. Model outputs are typically consumed through established analytics interfaces rather than a lightweight, self-serve modeling workflow.
Pros
- Peril-specific hazard and risk modeling workflows built for catastrophe scenarios
- Enterprise integration options for underwriting, portfolio, and risk analytics
- Robust scenario analysis for stress testing and exposure planning
Cons
- Model setup and governance can require specialized catastrophe expertise
- Workflow customization can feel constrained versus fully bespoke modeling tools
- Operational overhead can be high for small teams with limited integration needs
Best For
Insurance and reinsurance teams needing enterprise catastrophe modeling and scenario analysis
More related reading
OpenQuake Engine
open source engineRuns open source hazard and risk calculations for earthquakes with hazard assessment modules and loss estimation pipelines.
Logic-tree probabilistic hazard engine with ground-motion model selection and disaggregation
OpenQuake Engine stands out for its open, research-grade hazard modeling workflow built around standardized seismic and multi-hazard processes. It supports scenario and probabilistic earthquake hazard calculations, including logic trees, source models, ground-motion models, and site condition handling. The engine also produces risk-oriented outputs such as ground-shaking intensity measures and derived maps for decision workflows. Strong tooling centers on the OpenQuake job engine that executes calculations from defined inputs with reproducible results.
Pros
- Implements probabilistic earthquake hazard with logic-tree source and ground-motion model logic
- Generates consistent outputs for mapping, aggregates, and uncertainty handling
- Runs reproducible jobs from defined inputs via a dedicated calculation engine
- Supports scenario and disaggregation workflows for engineering-facing results
- Integrates site conditions and rupture and hazard parameterization
Cons
- Setup requires technical familiarity with model inputs and configuration formats
- Graphical UX is limited compared with commercial end-to-end platforms
- Large study runs demand careful tuning of performance and compute resources
- Advanced customization can require domain knowledge of seismic risk modeling concepts
Best For
Teams running reproducible earthquake hazard studies with engineering-grade control
HAZUS
scenario modelingProvides loss estimation and scenario tools for hazards using FEMA methodologies for earthquake, hurricane, and flood damage modeling.
Integrated FEMA HAZUS loss estimation linking hazard intensity to exposure damage and losses
HAZUS is distinct because it pairs FEMA risk assessment methodology with national-scale hazard and loss estimation models. It supports scenario modeling for earthquakes, floods, hurricanes, and other hazards by combining hazard intensity with building, population, and economic exposure. Core workflows include running standardized models, producing losses by asset and geography, and exporting tabular and GIS-ready outputs for reporting and decision support. Results align to FEMA guidance, making it useful for consistent catastrophe analyses across agencies and projects.
Pros
- Standardized FEMA methodology for consistent hazard and loss estimates
- Multihazard modeling supports buildings, populations, and economic impacts
- GIS-oriented outputs enable mapping, analysis, and stakeholder reporting
Cons
- Data preparation and calibration can be time-consuming
- Model setup complexity increases for custom exposure and scenarios
- Less flexible for non-FEMA modeling approaches and custom fragility logic
Best For
Agencies needing standardized FEMA catastrophe modeling with GIS-ready outputs
Quantitative Seismic Hazard Analysis Toolkit (OpenSHA)
seismic hazardSupports seismic hazard and risk calculations through an open source framework for executing model logic trees and hazard calculations.
OpenSHA’s extensible Java framework for PSHA source and ground-motion model composition
OpenSHA stands out by providing an open, extensible framework for quantitative seismic hazard analysis workflows rather than a closed hazard model app. It supports data management for earthquakes, faults, and ground-motion relationships, plus PSHA and related hazard computations with customizable logic. The toolkit includes tools for building hazard models, running analyses, and exporting results for downstream use cases like hazard map generation and risk-model inputs.
Pros
- Strong PSHA workflow support with modular hazard calculation components
- Extensible Java codebase enables custom models and logic branching
- Built-in utilities for organizing seismicity sources and hazard inputs
- Supports exporting hazard outputs for integration into other pipelines
Cons
- Programming-oriented workflow requires engineering effort for customization
- Model setup complexity can slow adoption for teams without domain specialists
- UI depth is limited compared with point-and-click catastrophe platforms
- Large study configurations can be heavy to manage and validate
Best For
Seismic engineering teams building customizable hazard models and map workflows
HURREVAC
hurricane hazardModels hurricane wind and related hazards for hazard assessment with parameterized hurricane track and intensity inputs.
Hurricane scenario modeling workflow designed for operational planning outputs
HURREVAC distinguishes itself with hurricane-focused modeling and science-first outputs tailored to emergency planning and risk communication. The core workflow supports building hurricane scenario inputs and generating hazard and impact style results for coastal exposure analysis. It emphasizes model transparency through visible assumptions and practical use for operational decision-making during storms. The tool is strongest for guided scenario runs rather than large-scale multi-model ensemble pipelines.
Pros
- Hurricane-specific scenario modeling with outputs aligned to planning use cases
- Focus on science-driven assumptions and transparent modeling steps
- Workflow supports generating usable results for coastal exposure assessments
Cons
- Limited evidence of broad multi-hazard support beyond hurricane modeling
- Less suited to automated large ensemble runs and complex batch pipelines
- Data preparation requires careful setup for credible scenario assumptions
Best For
Emergency planning teams running hurricane scenarios and coastal risk assessments
More related reading
Fathom Computational Framework
research analyticsProvides a computational environment for quantitative risk analytics and hazard modeling workflows used in research and decision support.
Workflow orchestration for connecting hazard inputs, scenario logic, and computed risk outputs
Fathom Computational Framework stands out by focusing on computational workflows for hazard and risk analysis rather than only report templates. The core capability is building catastrophe-modeling pipelines that connect inputs, scenario logic, and results into repeatable computation runs. It supports model execution for seismic and similar risk use cases through configurable workflows and structured outputs. The experience centers on integrating domain logic into a process framework that supports ongoing modeling iterations.
Pros
- Workflow-first design supports repeatable catastrophe modeling pipelines
- Configurable scenario logic enables complex hazard and impact computations
- Structured outputs improve traceability across modeling runs
- Computational framework encourages integration of custom model components
Cons
- Setup requires strong modeling and workflow configuration expertise
- User experience can feel technical versus GUI-first catastrophe tools
- Collaboration and review tooling for outputs is limited versus dedicated platforms
Best For
Teams building custom catastrophe modeling workflows and automated scenario runs
EMDAT
disaster databaseSupplies disaster event data and tools that support catastrophe modeling research through standardized disaster occurrence records.
EMDAT’s standardized disaster event database for harmonized global hazard and impact records
EMDAT is distinct for its catastrophe event database focus, centered on globally standardized disaster occurrence and impact recording. Core capabilities include event selection, hazard and impact filtering, and exporting structured datasets for risk and loss analysis workflows. The tool supports modeling-adjacent use cases by enabling analysts to assemble consistent historical event samples across countries and disaster types. Data granularity and predefined classifications drive reproducibility, while advanced scenario generation and custom model building remain limited compared with full modeling engines.
Pros
- Standardized disaster event records improve repeatable catastrophe modeling inputs
- Powerful filtering by hazard type, location, and time supports targeted event sampling
- Exports enable direct integration into analysis pipelines and downstream modeling tools
Cons
- Limited support for custom hazard scenario generation beyond database retrieval
- Data preparation and mapping effort can be significant for specialized modeling schemas
- Modeling-grade parameterization and simulation controls are not the main focus
Best For
Teams using historical disaster event datasets for catastrophe model calibration and validation
AEL
cat modelingProvides specialized catastrophe modeling software and services for risk analytics used in insurance and research workflows.
Scenario-run management for comparing catastrophe model outputs across iterations
AEL stands out with a catastrophe modeling workflow centered on building, running, and analyzing risk scenarios for decision support. Core capabilities include hazard modeling inputs, exposure data handling, and portfolio-level loss outputs tied to modeled peril behavior. The tooling supports iterative calibration and reporting so teams can compare scenario runs and communicate impacts across stakeholders. The platform also emphasizes structured data preparation and repeatable modeling runs instead of purely interactive analytics.
Pros
- Structured hazard and exposure workflow supports repeatable catastrophe scenario runs
- Portfolio-level outputs align with common risk review and underwriting reporting needs
- Iterative scenario comparison helps validate assumptions and track changes
Cons
- Model setup and data preparation require strong domain process discipline
- Interactive exploration is less prominent than scenario-driven modeling pipelines
- Limited evidence of broad self-serve integrations for external data sources
Best For
Risk teams producing repeatable catastrophe scenario results for portfolios
How to Choose the Right Catastrophe Modeling Software
This buyer’s guide helps teams pick Catastrophe Modeling Software tools that match their hazard focus, output needs, and workflow style. It covers Verisk, OpenQuake Engine, HAZUS, OpenSHA, HURREVAC, Fathom Computational Framework, EMDAT, and AEL, along with practical selection patterns derived from their real strengths and limitations. The guide also explains common mistakes like forcing the wrong modeling scope and underestimating setup and governance overhead.
What Is Catastrophe Modeling Software?
Catastrophe Modeling Software runs hazard and vulnerability workflows to estimate impacts like loss and damage from extreme events. These tools connect scenario inputs, exposure data, and model logic to produce outputs used in underwriting support, emergency planning, and risk analytics. Verisk exemplifies enterprise catastrophe workflows that integrate hazard, exposure processing, and scenario-based risk quantification into decisioning interfaces. OpenQuake Engine exemplifies an engineering-grade earthquake hazard engine that produces reproducible probabilistic hazard outputs using logic trees, ground-motion model selection, and disaggregation.
Key Features to Look For
Catastrophe modeling software earns adoption when its workflow matches the event science, the exposure scope, and the required output format.
Peril-specific integrated hazard, exposure, and scenario risk quantification
Verisk excels at peril-specific hazard and risk modeling workflows that combine hazard, exposure processing, and scenario analysis for stress testing and exposure planning. AEL supports a scenario-run workflow that produces portfolio-level loss outputs tied to modeled peril behavior, which helps compare iterations for decision support.
Logic-tree probabilistic hazard with disaggregation and uncertainty handling
OpenQuake Engine provides a logic-tree probabilistic hazard engine with ground-motion model selection and disaggregation. OpenSHA supports PSHA workflows through an extensible Java framework that composes source models and ground-motion relationships for customizable hazard computations.
Standardized methodology workflows for FEMA-aligned loss estimation
HAZUS links hazard intensity to exposure damage and losses using FEMA methodologies across earthquakes, hurricanes, and floods. The tool produces GIS-ready outputs that support mapping, analysis, and stakeholder reporting aligned to FEMA guidance.
Scenario modeling designed for operational emergency planning outputs
HURREVAC focuses on hurricane scenario inputs and generates hazard and impact style results aligned to coastal exposure analysis and emergency planning. Its workflow emphasizes transparent assumptions and practical use during storms rather than large automated ensemble pipelines.
Workflow orchestration for repeatable catastrophe-modeling pipelines
Fathom Computational Framework is built for repeatable computation runs by connecting hazard inputs, scenario logic, and computed risk outputs into a workflow-first framework. It supports configurable scenario logic and structured outputs to improve traceability across modeling iterations.
Harmonized historical disaster event datasets for calibration and validation
EMDAT supplies standardized disaster event records and enables hazard type, location, and time filtering for consistent historical samples. It supports exports that integrate into downstream analysis and risk workflows for model calibration and validation.
How to Choose the Right Catastrophe Modeling Software
A practical selection starts by matching hazard scope and output workflow to the specific catastrophe science and decision use case.
Match the tool to the hazard types and modeling standard required
Choose HAZUS for multihazard loss estimation workflows aligned to FEMA methodology across earthquakes, hurricanes, and floods with GIS-ready outputs. Choose HURREVAC for hurricane-focused scenario modeling that supports emergency planning and coastal risk assessment outputs built around visible assumptions.
Pick the modeling approach based on reproducibility and customization needs
Choose OpenQuake Engine for reproducible earthquake hazard studies driven by logic-tree source models, ground-motion model selection, and disaggregation results. Choose OpenSHA when teams need extensible Java-based PSHA model building with modular hazard calculation components and custom logic branching.
Select the workflow style based on how decisions get made inside the organization
Choose Verisk when enterprise catastrophe modeling outputs need to flow into underwriting, portfolio exposure planning, and risk analytics through established integration interfaces. Choose AEL when repeatable scenario-run management and portfolio-level loss outputs for stakeholder communication drive the modeling process.
Ensure the tool fits the team’s data pipeline and compute realities
Choose OpenQuake Engine or OpenSHA when long-running study runs require careful tuning of compute resources and configuration to maintain correct input and uncertainty handling. Choose HAZUS when the organization can support FEMA-aligned data preparation and scenario setup complexity for consistent nationwide outputs.
Plan for repeatability, traceability, and iteration management across runs
Choose Fathom Computational Framework when repeatable computation runs depend on workflow orchestration that connects inputs, scenario logic, and computed risk outputs into structured pipelines. Choose AEL when comparing scenario runs across iterations and producing portfolio-ready loss outputs is central to review and decision cycles.
Who Needs Catastrophe Modeling Software?
Catastrophe Modeling Software is most effective when the organization’s main work is scenario execution, hazard and loss analytics, or calibration to historical event behavior.
Insurance and reinsurance teams needing enterprise catastrophe modeling and scenario analysis
Verisk fits this need because it supports enterprise hazard and vulnerability modeling, exposure processing, and scenario-based loss analytics built for underwriting support and portfolio exposure planning. AEL also fits teams that prioritize repeatable scenario runs and portfolio-level outputs for risk review and underwriting reporting.
Earthquake hazard study teams focused on reproducible engineering-grade outputs
OpenQuake Engine fits this need because it runs logic-tree probabilistic earthquake hazard calculations with ground-motion model selection, site conditions, and disaggregation using a dedicated job engine. OpenSHA fits teams that need an extensible Java framework to build customizable PSHA models and export hazard outputs into downstream pipelines.
Agencies and organizations requiring FEMA methodology and GIS-ready multihazard outputs
HAZUS fits because it pairs standardized FEMA risk assessment methodology with loss estimation across earthquakes, floods, and hurricanes. It also generates GIS-oriented outputs for mapping, stakeholder reporting, and consistent hazard-to-loss linking.
Emergency planning teams running hurricane scenarios for coastal exposure analysis
HURREVAC fits because it is designed for hurricane scenario modeling and planning outputs that emphasize operational decision-making during storms. Its guided scenario workflow supports credible coastal risk results without requiring broad multi-hazard ensemble pipeline complexity.
Common Mistakes to Avoid
The most frequent buying failures come from mismatching hazard scope, under-scoping the setup effort, and expecting GUI convenience from engines built for technical control.
Assuming hurricane-focused scenario tools cover multihazard catastrophe modeling
HURREVAC is strongest for hurricane scenario modeling and coastal exposure analysis, and it provides limited evidence of broad multi-hazard support beyond hurricane modeling. Selecting HAZUS instead aligns the workflow with FEMA multihazard modeling for earthquakes, floods, and hurricanes and avoids forcing hurricane-only logic into other hazard domains.
Buying a research-grade engine and expecting point-and-click catastrophe UX
OpenQuake Engine provides graphical UX that is limited compared with commercial end-to-end platforms because it centers on its job engine and reproducible inputs. OpenSHA similarly uses a programming-oriented workflow with engineering effort for customization, so expecting a lightweight interface leads to slow adoption and rework.
Underestimating data preparation effort for standardized methodologies and event schemas
HAZUS requires time-consuming data preparation and more complex model setup when custom exposure and scenarios are needed. EMDAT exports standardized disaster event records but still requires data preparation and mapping effort for specialized modeling schemas.
Choosing a workflow-first framework without workflow configuration capability
Fathom Computational Framework requires strong modeling and workflow configuration expertise because the experience is technical and workflow-first rather than GUI-first. AEL also depends on structured data preparation and domain process discipline for reliable scenario run outputs.
How We Selected and Ranked These Tools
we evaluated every tool on three sub-dimensions with features weighted 0.4, ease of use weighted 0.3, and value weighted 0.3. The overall rating is the weighted average of those three dimensions using overall = 0.40 × features + 0.30 × ease of use + 0.30 × value. Verisk separated from lower-ranked tools by scoring strongly on features because it delivers an integrated catastrophe model workflow for hazard, exposure processing, and scenario-based risk quantification targeted at underwriting and portfolio exposure planning.
Frequently Asked Questions About Catastrophe Modeling Software
How do Verisk and AEL differ for enterprise catastrophe modeling workflows?
Verisk centers on hazard modeling tied to an enterprise-grade data and analytics ecosystem, with outputs typically consumed through established analytics interfaces. AEL emphasizes scenario-run management for comparing catastrophe model outputs across iterations, with structured data preparation and repeatable portfolio loss outputs.
Which tool fits reproducible earthquake hazard calculations with engineering-grade controls?
OpenQuake Engine runs logic-tree probabilistic earthquake hazard calculations using defined inputs and an OpenQuake job engine for reproducible results. OpenSHA provides an open, extensible Java framework for customizable PSHA workflows, including logic construction and ground-motion model composition.
When is HAZUS the right choice for standardized catastrophe risk assessment?
HAZUS pairs FEMA risk methodology with national-scale hazard and loss estimation by linking hazard intensity to building, population, and economic exposure. It produces GIS-ready and tabular outputs for standardized scenario modeling across multiple hazards like earthquakes, floods, and hurricanes.
Which software supports hurricane scenario inputs for emergency planning and risk communication?
HURREVAC is built around hurricane scenario modeling that generates operational planning outputs for coastal exposure analysis. It emphasizes visible assumptions and practical use for guided scenario runs instead of large-scale multi-model ensemble pipelines.
What should teams look for if the goal is automating catastrophe modeling pipelines?
Fathom Computational Framework focuses on workflow orchestration that connects hazard inputs, scenario logic, and computed risk outputs into repeatable runs. This model-execution workflow approach contrasts with EMDAT, which centers on building harmonized historical disaster event datasets rather than executing full hazard and risk computations.
How do OpenQuake Engine and OpenSHA handle hazard model logic and ground-motion selection?
OpenQuake Engine supports probabilistic earthquake hazard calculations using logic trees and explicit choices for source models, ground-motion models, and site conditions. OpenSHA provides an extensible Java toolkit for composing PSHA source and ground-motion model logic, plus exporting hazard maps and downstream risk-model inputs.
Which tool is best for calibrating and validating catastrophe models using historical event records?
EMDAT provides a globally standardized catastrophe event database with consistent classifications that support selecting events and filtering by hazard and impact. This dataset-first approach is useful for model calibration and validation, while OpenQuake Engine and HAZUS execute forward hazard and loss calculations from technical inputs.
What common data products can GIS and reporting workflows expect from HAZUS and OpenQuake Engine?
HAZUS exports GIS-ready and tabular results by asset and geography for scenario losses aligned to FEMA guidance. OpenQuake Engine produces risk-oriented outputs such as ground-shaking intensity measures and derived maps that can feed decision workflows.
Which software is better aligned to portfolio-level scenario comparisons rather than single runs?
AEL is designed for iterative calibration and reporting that compares scenario runs and communicates portfolio impacts across stakeholders. Verisk can support scenario analysis for underwriting and portfolio exposure planning, but it typically integrates outputs into an enterprise analytics environment rather than operating like a lightweight scenario-run workspace.
Conclusion
After evaluating 8 science research, Verisk stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
Tools reviewed
Referenced in the comparison table and product reviews above.
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