CVA: Rethinking inputs for greater accuracy and efficiency
Traditional CVA pricing often relies on incomplete or proxy data, especially for unrated or private counterparties – leading to inaccuracies in capital, risk and pricing decisions.
Credit Benchmark offers a smarter alternative.
Download our CVA Explainer to learn how trading teams can:
- Replace patchy CDS and proxy data with real-world PDs
- Integrate Credit Benchmark into their CVA input waterfall
- Improve capital efficiency and regulatory outcomes
LEARN MORE
CVA: APPLICATIONS OF CREDIT CONSENSUS RATINGS
CVA: Rethinking inputs for greater accuracy and efficiency
Traditional CVA pricing often relies on incomplete or proxy data, especially for unrated or private counterparties – leading to inaccuracies in capital, risk and pricing decisions.
Credit Benchmark offers a smarter alternative.
Download our CVA Explainer to learn how trading teams can:
- Replace patchy CDS and proxy data with real-world PDs
- Integrate Credit Benchmark into their CVA input waterfall
- Improve capital efficiency and regulatory outcomes
LEARN MORE
CVA: APPLICATIONS OF CREDIT CONSENSUS RATINGS
Credit Benchmark aggregates internal credit risk views from 40+ global banks.
This creates forward-looking, real-world Probability of Default (PD) estimates.
These data points are:
✓ Updated weekly
✓ Regulator-friendly
✓ Easy to integrate
✓ Designed to fill gaps in CDS, bond,
and CRA coverage
Your Challenge
With Credit Benchmark
Missing CDS / Bond Spreads
Fill the gap with PDs from real bank views
Unrated or Private Counterparties
Coverage of 115,000+ names (90% unrated)
Regulatory Pressure
Regulator-ready, transparent methodology
Siloed internal data
External source avoids classification issues
Inefficient capital allocation
More precise inputs = smarter risk weighting
Your Challenge
With Credit Benchmark
Missing CDS / Bond Spreads
Fill the gap with PDs from real bank views
Unrated or Private Counterparties
Coverage of 115,000+ names (90% unrated)
Regulatory Pressure
Regulator-ready, transparent methodology
Siloed internal data
External source avoids classification issues
Inefficient capital allocation
More precise inputs = smarter risk weighting
The CVA Input Waterfall
Banks often use a “waterfall” approach to data sourcing. A common order of preference:
- CDS
- Bonds
- CRA Ratings
- Proxy Matrices
- CRA Ratings
- Bonds
With Credit Benchmark (Fits in cleanly, no model overhaul required):
- CDS
- Bonds
- Credit Benchmark Probability of Default
- CRA Ratings
- Proxy Matrices
- CRA Ratings
- Credit Benchmark Probability of Default
- Bonds
Smarter CVA decisions with better credit data.
✓ 5 x the coverage of major CRAs
✓ 90% of entites unrated elsewhere
✓ Weekly updates available
✓ Trusted by major global banks
Credit Benchmark brings together internal credit risk views from over 40 leading global financial institutions. The contributions are anonymized, aggregated, and published in the form of consensus ratings and aggregate analytics to provide an independent, real-world perspective of credit risk. Risk and investment professionals at banks, insurance companies, asset managers and other financial firms use the data for insights into the unrated, monitoring and alerting within their portfolios, benchmarking, assessing and analyzing trends, and fulfilling regulatory requirements and capital.
