Analyzing Credit Rating Advisory

SkillProductivity

Prepares credit rating agency presentations with methodology alignment, peer positioning, and target rating analysis. Use when advising on credit ratings, preparing rating agency meetings, or analyzing rating methodology impact.

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What this skill tells your AI

The instructions your AI receives, as published by casemark/skills in skills/capital/analyzing-credit-rating-advisory/SKILL.md and read by ahel’s review.

When To Use

  • Preparing for an initial or annual rating agency meeting (S&P, Moody's, Fitch, KBRA, DBRS)
  • Advising an issuer on achieving or maintaining a target credit rating
  • Assessing how a proposed transaction (M&A, recapitalization, dividend recap, spin-off) will impact an existing rating
  • Building a peer comparison framework to support a rating upgrade or defend against a downgrade
  • Mapping issuer financials to agency-specific methodology scorecards

Inputs To Gather

  • Issuer financials: 3–5 years of historical audited financials plus current-year projections and management forecasts
  • Target agency and methodology: Confirm which agency (or agencies) and which published methodology/criteria document applies (e.g., S&P Corporate Methodology, Moody's Financial Services Rating Methodology) [VERIFY which methodology version is current]
  • Existing rating and outlook: Current rating, outlook, and any recent rating action commentary
  • Capital structure detail: Full debt stack with maturities, rates, covenants, and any off-balance-sheet obligations
  • Peer group: 5–10 comparable issuers with publicly available ratings and financial data
  • Transaction specifics (if applicable): Pro forma capital structure, sources & uses, synergy assumptions, integration timeline
  • Management credit story: Strategic narrative the issuer wants to convey (deleveraging path, margin expansion, portfolio stability)

Workflow

  1. Map the methodology scorecard

    • Identify each rating factor and subfactor from the applicable agency methodology
    • Note weightings (explicit for Moody's scorecards; qualitative for S&P's blended approach)
    • Flag any sector-specific adjustments or notching criteria (diversification, country risk, governance) [VERIFY notching rules per current criteria]
  2. Score the issuer on each factor

    • Calculate key credit metrics the agency emphasizes: Debt/EBITDA, FFO/Debt, EBITDA/Interest, Free Cash Flow/Debt, EBITDA margin
    • Assess qualitative factors: business risk profile, competitive position, industry risk, management and governance
    • Assign an indicative rating category per factor using the agency's published thresholds
  3. Build the peer positioning matrix

    • Compile comparable metrics for the peer group from public filings and rating reports
    • Position the issuer relative to peers on both quantitative metrics and qualitative assessments
    • Highlight where the issuer outperforms peers at the same or adjacent rating level — these are upgrade arguments
    • Flag where the issuer underperforms — these require defensive narrative
  4. Develop the target rating analysis

    • Determine the gap between the issuer's current indicated score and the target rating threshold
    • Identify which 2–3 factors have the most leverage to close the gap (e.g., a 0.5x reduction in Debt/EBITDA may move the financial risk factor one category)
    • Model a realistic timeline: what metrics must the issuer hit, by when, to support the target rating
    • For transaction scenarios, build a pro forma scorecard showing Day 1 impact and the glide path to target metrics
  5. Draft the rating agency presentation

    • Executive summary: Company overview, credit highlights, rating request or objective
    • Business risk profile: Industry dynamics, market position, revenue diversification, competitive advantages
    • Financial risk profile: Historical and projected credit metrics, capital allocation policy, liquidity analysis
    • Peer comparison: Side-by-side metric tables with commentary on relative positioning
    • Management financial policy: Stated leverage targets, shareholder return policy, M&A philosophy
    • Scenario and sensitivity analysis: Downside cases showing covenant and rating metric headroom
  6. Prepare Q&A anticipation memo

    • List the 10–15 most likely analyst questions based on methodology focus areas and recent agency commentary
    • Draft recommended management responses that reinforce the credit story
    • Identify sensitive topics (customer concentration, regulatory risk, pending litigation) and prepare positioning language

Output

  • Methodology scorecard mapping with factor-by-factor indicative ratings and commentary
  • Peer comparison matrix with quantitative and qualitative positioning
  • Rating agency presentation deck structured per the workflow above
  • Q&A anticipation memo with recommended responses
  • Target rating bridge showing metric gaps and timeline to achieve target

Quality Checks

  • Every quantitative metric ties back to audited financials or clearly labeled projections — no orphaned numbers
  • Methodology version cited is the most recently published [VERIFY publication date against agency website]
  • Peer data is sourced from the same fiscal period for comparability; any mismatches are disclosed
  • Pro forma adjustments are clearly labeled and reconcilable to sources & uses
  • Presentation narrative is consistent with the issuer's public disclosures — no forward-looking statements that contradict filed documents
  • Metric definitions match the agency's published definitions (e.g., S&P-adjusted debt includes operating leases and pensions; Moody's standard adjustments may differ) [VERIFY agency-specific adjustment conventions]
  • Sensitivity scenarios use stress assumptions consistent with the agency's own stress-testing guidance
  • All rating factor assessments include the basis for the assigned category, not just the conclusion

Signals

GitHub stars
41
Forks
15
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
analyzing-credit-rating-advisory
Source
github.com/casemark/skills