Evaluate financial health, performance, and trends before making informed investment decisions. Track ongoing credit exposures with automated financial spreading and publishing.
Building upon the powerful Aerlytix technology suite, Credit Risk is a comprehensive risk management platform driven by your proprietary credit scoring methodologies and enriched by intelligence sources chosen by you.
The platform offers the scale and scope to complete deep credit risk analysis and evaluations of your global counterparties, all within one interface.
The Credit Risk Knowledge Base gives Risk Managers a centralized location to store all qualitative and quantitative risk-relevant information.
This data can be uploaded directly from internal sources or seamlessly integrated with third-party sources, such as ISHKA and Airfinance Global.
Non-financial counterparty attributes can also be added to build a comprehensive risk profile.
Proprietary risk methodologies defined by you are applied to your data with flexibility to adjust and customize based on your specific needs and insights.
Advanced calculation models are automated based on your unique inputs, giving you your own credit profiles and risk ratings, published within the centralized platform for further analysis. Detailed dashboarding and exception-based reporting is available as standard.
Credit Risk is available standalone or seamlessly integrated into the Aerlytix Analytics Suite.
Integrated users can run enhanced reporting on a credit adjusted basis, including aircraft recovery model forecasts and lessee default models.
Portfolio-level exposure analytics can be gained through the seamless integration with Aerlytix's industry-leading maintenance cashflow and valuations analytics.
AI accelerates analysis, improves data usability, and unlocks additional layers of insight to support confident, human-led decision-making.
Artificial intelligence enhances our platform capabilities, evolving how users interact with data, models, and insights.
Aerlytix leverages AI-driven parsing to transform financial statements into structured, usable data.
Rapid digitization of historically manual inputs
Improved data completeness and accuracy