Cardo AI, a technology platform for asset-based finance (ABF) and private credit, has introduced unified data standards covering 30 asset classes. The new framework establishes a common language for lenders and investors across consumer and corporate exposures.
The asset reference library includes 11 consumer asset classes and 19 corporate asset classes. These asset classes constitute around $5.8 trillion of the asset-based financing market. In addition, the standards offer a standardized way to analyze and manage collateral.
Creating Consistency Across Asset-Based Finance
Each one contains critical information about assets such as eligibility criteria, covenants, payment waterfall, and monitoring. Furthermore, the structure makes use of open formulas where all calculations can be traced from data sources to outcomes.
All 30 standards follow one shared data model. Consequently, lenders and investors can assess transactions across different asset classes using consistent definitions and calculation methods.
Historically, the asset-backed finance market has been a distinct market segment having its own distinct approach and terminology. However, this fragmentation could hinder the process of onboarding deals and increase difficulties.
These are some of the problems that the new asset-based finance data standards try to solve. Through creating standardized definitions and regulations, Cardo AI allows market participants to assess deals in a uniform manner. Moreover, calculations can be traced back to their underlying data sources.
“I have frequently seen good deals stall simply because the two sides interpreted the underlying collateral data differently,” comments Altin Kadareja, Co-Founder and CEO of Cardo AI. “We built these standards so that a loan tape, a covenant, or a waterfall calculation means the exact same thing to everyone reviewing it, regardless of the underlying asset class.”
Supporting Transparent Deal Evaluation
The structure is applicable to various kinds of collateral, such as consumer lending, airplanes, and music royalties. This makes it possible for lenders and institutional investors to evaluate the various financing alternatives within a uniform structure.
Standardized data may also make due diligence and comparisons between portfolios easier. On the other hand, consistency in calculations can help companies avoid inconsistencies when analyzing collateral data.
Each asset-class standard will be made available to lenders and investors by Cardo AI upon request. The package will comprise the shared data model, an asset class extension, and entities/field definitions.
In addition, there is also an example of working on a pool of assets. In this way, one gets to see how the standard applies to real-world finance cases. It’s doing so, Cardo AI seeks to enhance data consistency in asset-based finance. Eventually, the standards will give lenders and investors something to base their comparisons on.
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News Source: Businesswire.com
