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 "name": "Rating Inflation Qualifies Monitoring Layer Moral Hazard",
 "text": "Bolton, Freixas, and Shapiro qualify Kaal's treatment of over-approval as moral hazard in the monitoring layer. Their model places the conflict inside the rating agency. The agency can understate credit risk to attract business, while issuers can purchase only favorable ratings. Rating inflation becomes more likely when reputation costs are lower or more investors accept ratings at face value. The monitor's verdict can therefore become more favorable even when the underlying risk remains unchanged. This correspondence supports Kaal's classification of over-approval as an incentive failure by the adjudicator rather than merely an error by the worker being evaluated.\n\nThe comparison is bounded. Credit rating agencies evaluate securities, not LLM-generated task outputs. The source models reported credit risk rather than approval against a known task-level ground truth. It does not test Kaal's validation pool or establish any measured over-approval rate. It supplies an independently developed mechanism for favorable verdicts to decouple from the quality the monitor is expected to assess. Kaal's empirical application remains a separate proposition.",
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  "name": "Wulf A. Kaal",
  "identifier": "https://orcid.org/0009-0008-7840-1847"
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  "Mapping review tier: independent substantive scholarly-growth qualification.",
  "The paper studies credit rating agencies and securities, not LLM validation pools.",
  "Its model concerns reported credit risk rather than approval against known task-level ground truth.",
  "It does not estimate Kaal's over-approval measure or establish any registered empirical result.",
  "The complete public NBER working paper was reviewed. Semantic Scholar returned no DOI record, so no Semantic Scholar evidence was promoted.",
  "Fresh English, German, and Spanish Crossref and OpenAlex discovery was completed. Semantic Scholar search returned HTTP 429."
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  "name": "The Credit Ratings Game",
  "url": "https://www.nber.org/system/files/working_papers/w14712/w14712.pdf"
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  "url": "https://wulfkaal.github.io/claims/7261018-018",
  "citation": "Wulf A. Kaal, Empirical Evaluation of the Agentic Reputation Substrate: Deliberation, the Composition of Error, and the Registered Measurement of Agency Costs in a Controlled Multi-Model Cohort (2026). SSRN: https://ssrn.com/abstract=7261018",
  "paper": "Wulf A. Kaal, Empirical Evaluation of the Agentic Reputation Substrate: Deliberation, the Composition of Error, and the Registered Measurement of Agency Costs in a Controlled Multi-Model Cohort",
  "authors": [
   "Wulf A. Kaal"
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  "sourceProposition": "Bolton, Freixas, and Shapiro model a rating agency that can understate credit risk to attract business. Rating inflation becomes more likely when investors take ratings at face value or the agency's expected reputation costs are lower. This supports the narrow proposition that incentive conflicts inside an evaluator can make its verdicts systematically more favorable than the underlying risk warrants. It does not test Kaal's validation pool, task-level ground truth, LLM agents, or any empirical over-approval rate.",
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