External benchmarking to strengthen internal IG/Non-IG classifications and inform capital decisions under the proposed US ERBA

Why external evidence matters under US ERBA

Under the proposed US Expanded Risk-Based Approach (ERBA)*, qualifying investment-grade (IG) corporate exposures could receive a 65% risk weight, compared with a general 100% risk weight. To receive this treatment, IG classifications must be determined through an internal rating system meeting the proposed requirements, including use in material business and risk decisions and at least annual validation with external benchmarking of IG obligor ratings. External benchmarking is not limited to agency ratings; banks can also consider other external credit information.

Broader evidence for your credit classifications

The RPx Credit Classification Benchmark compares your bank’s IG and non-investment-grade (Non-IG) classifications with those of other bank contributors for the same obligors. Each bank’s own rating scale determines its classification. The comparison reveals where your assessments differ and identifies recurring patterns across grades, sectors and models. This adds lender perspectives to external benchmarking alongside agency ratings and third-party model-based assessments.

What Credit Benchmark adds

• Multiple lender perspectives. See how other bank contributors classify the same obligor and how strongly their assessments support or differ from yours.
• Broader coverage. Extend the external evidence available for review, including for comparable obligors without agency ratings and other portfolio segments where evidence is limited.
• A focus for action. Identify and prioritize recurring differences across grades, sectors or models, supporting IG challenge and review of potential capital relief within your Non-IG population.

How much more of your portfolio could be reviewed?

Compare contributor coverage with agency coverage to see where lender evidence can extend external review. In this example, 800 of the 1,000 comparable obligors have no agency rating.

Where could your Non-IG classifications warrant review?

A population to review. Your bank classifies these 160 obligors as Non-IG, while a majority of other contributors classify them as IG. Investigating recurring differences can identify where a supported reassessment may have capital implications.

Why do these G5 classifications differ? Review the wider G5 population to establish whether differences are systematic and whether model outputs, overrides or grade mappings help explain them.

The reverse comparison identifies your IG obligors that other contributors predominantly classify as Non-IG, supporting external benchmarking and challenge.

Turn recurring differences into a structured review

• Locate concentrations. Compare grades, sectors and, where supplied, models by counts and the percentage of comparable obligors with majority disagreement.
• Investigate the basis. Review credit assessments, grade mappings, and overrides to understand why classifications differ.
• Assess capital implications. Use exposure and eligibility data to estimate RWA effects where a supported review leads to revised classifications.
• Strengthen ongoing challenge. Track recurring differences and review outcomes, adding lender evidence to existing validation and governance processes.

Evidence for informed decisions

The RPx Credit Classification Benchmark brings multiple lender perspectives to support external benchmarking and broader validation efforts under the proposed US ERBA. It extends Credit Benchmark’s service into classification review, helping banks investigate material differences across affected populations and make informed classification and capital decisions.