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The Informational Content of Bank Risk Weights and the Role of Internal Ratings

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  • Brunella Bruno, Francesco Corielli, Immacolata Marino, Giacomo Nocera

Abstract

We examine when a regulatory measure of bank asset risk, the ratio of risk-weighted assets to total assets (RWATA), aligns with a market-based measure of risk, namely the volatility of bank assets estimated using option-pricing techniques. We argue that the informational content of RWATA is conditional on the framework used to generate risk weights. Using a unique hand-collected dataset on the adoption and scope of internal ratings-based (IRB) models, we show that RWATA is unrelated to market-based asset risk on average, but becomes significantly associated with asset volatility among banks that use internal models. The relationship strengthens with the intensity of IRB adoption, particularly when advanced internal models are applied to corporate exposures, and persists among relatively weakly capitalized banks and during periods of financial stress.

Suggested Citation

  • Brunella Bruno, Francesco Corielli, Immacolata Marino, Giacomo Nocera, 2026. "The Informational Content of Bank Risk Weights and the Role of Internal Ratings," BAFFI CAREFIN Working Papers 26281, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    • Handle: RePEc:baf:cbafwp:cbafwp26281
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    References listed on IDEAS

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    1. Ms. Sofiya Avramova & Mrs. Vanessa Le Lesle, 2012. "Revisiting Risk-Weighted Assets," IMF Working Papers 2012/090, International Monetary Fund.
    2. Bruno, Brunella & Nocera, Giacomo & Resti, Andrea, 2017. "Are risk-based capital requirements detrimental to corporate lending? Evidence from Europe," CEPR Discussion Papers 12007, Centre for Economic Policy Research.
    3. Flannery, Mark J & Sorescu, Sorin M, 1996. "Evidence of Bank Market Discipline in Subordinated Debenture Yields: 1983-1991," Journal of Finance, American Finance Association, vol. 51(4), pages 1347-1377, September.
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    5. Acharya, Viral & Engle, Robert & Pierret, Diane, 2014. "Testing macroprudential stress tests: The risk of regulatory risk weights," Journal of Monetary Economics, Elsevier, vol. 65(C), pages 36-53.
    6. Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2017. "Measuring Systemic Risk," The Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 2-47.
    7. Bruno, Brunella & Marino, Immacolata & Nocera, Giacomo, 2023. "Internal ratings and bank opacity: Evidence from analysts’ forecasts," Journal of Financial Intermediation, Elsevier, vol. 56(C).
    8. Brunella Bruno & Immacolata Marino & Giacomo Nocera, 2020. "Internal Ratings, Non-Performing Loans, and Bank Opacity: Evidence from Analysts’ Forecasts," CSEF Working Papers 576, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy, revised 25 Jan 2023.
    9. Mariathasan, Mike & Merrouche, Ouarda, 2014. "The manipulation of basel risk-weights," Journal of Financial Intermediation, Elsevier, vol. 23(3), pages 300-321.
    10. Viral Acharya & Robert Engle & Matthew Richardson, 2012. "Capital Shortfall: A New Approach to Ranking and Regulating Systemic Risks," American Economic Review, American Economic Association, vol. 102(3), pages 59-64, May.
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    Keywords

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    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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