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ease
features
design
support

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Write a Review

Description

Moody's Intelligent Risk Platform™ (IRP) is a cloud-based solution crafted to improve risk evaluation and decision-making processes for insurers, reinsurers, and brokers alike. Drawing on more than three decades of experience in risk analytics, this platform incorporates leading Moody's RMS™ models to deliver comprehensive insights into a range of hazards, including both natural disasters and human-induced events. Its modular design presents a collection of applications—such as Risk Modeler™, UnderwriteIQ™, TreatyIQ™, and ExposureIQ™—that optimize workflows throughout the insurance value chain, spanning from underwriting to portfolio management. Hosted on Amazon Web Services (AWS), the IRP guarantees scalability, adaptability, and a commitment to ongoing innovation, with updates introduced every six weeks. Furthermore, the platform is compatible with over 700 third-party and proprietary models, thanks to its Open Modeling Engine, which promotes a cohesive approach to multi-vendor risk modeling. Ultimately, this innovative solution empowers users to make more informed decisions, aligning risk management strategies with the dynamic nature of the market.

Description

The Oasis Loss Modelling Framework (Oasis LMF) serves as an open-source platform for catastrophe modeling that aims to improve risk assessment through its commitment to transparency, performance, and innovation. Founded as a not-for-profit entity, Oasis LMF provides a wide array of tools for the creation, deployment, and operation of catastrophe models, allowing for flexibility in modeling methods. The platform features a user-friendly web interface and an API that ensures easy integration with various systems, enhancing interoperability and user experience. Key components like Oasis ktools facilitate the large-scale execution of catastrophe models, while the Oasis Model Development Toolkit aids in the creation and testing of new models. With a strong focus on collaboration within the community, Oasis LMF boasts an ecosystem that includes over 18 suppliers and more than 90 different models, promoting a rich and varied modeling landscape. This diverse array of resources underscores the platform's mission to support users in navigating the complexities of risk assessment in an ever-evolving environment.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Dataoorts GPU Cloud Yes 
HurLoss No 
TreatyIQ Yes 

Integrations

Dataoorts GPU Cloud No 
HurLoss Yes 
TreatyIQ No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person Yes 

Vendor Details

Company Name

Moody's Corporation

Founded

1909

Country

United States

Website

www.moodys.com/web/en/us/who-we-serve/insurance/intelligent-risk-platform.html

Vendor Details

Company Name

Oasis Loss Modelling Framework

Founded

2012

Country

United Kingdom

Website

oasislmf.org

Product Features

Risk Management

Alerts/Notifications No 
Auditing No 
Business Process Control No 
Compliance Management No 
Corrective Actions (CAPA) No 
Dashboard No 
Exceptions Management No 
IT Risk Management No 
Internal Controls Management No 
Legal Risk Management No 
Mobile Access No 
Operational Risk Management No 
Predictive Analytics No 
Reputation Risk Management No 
Response Management No 
Risk Assessment No 

Product Features

Alternatives

Alternatives

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