How the C100 Score and CIP Grade are derived.

1 · Master formula

C100Score =
    0.25 · norm(A)              // Carbon Activity
  + 0.15 · norm(Q)              // Credit Quality Exposure
  + 0.20 · norm(E)              // ESG & Climate Compliance
  + 0.15 · norm(T)              // Transition Execution
  + 0.10 · norm(F)              // Financial & Market Strength
  + 0.10 · ( 100 − norm(R) )    // Sentiment Integrity  (Risk inverted)
  + 0.05 · norm(N)              // Innovation Premium

  ──────────────────────────────────────────────────
  Result clamped to [0, 100]   ·   weights sum to 1.0

Each raw component X is normalized into norm(X) ∈ [0, 100] using a percentile rank against the active C100 cohort. The risk component R is inverted because it measures downside, not strength.

2 · The seven pillars

3 · Normalization

Raw component inputs (volumes, counts, ratings) live on incompatible scales, so each is mapped into a 0–100 percentile against the active C100 cohort:

norm(X_i)  =  100 · ( rank(X_i) − 1 )  /  ( N − 1 )

where:
  X_i      = raw value for company i on component X
  rank()   = ascending rank within the cohort (ties share the average rank)
  N        = number of companies with a non-null value for component X

Missing inputs are not imputed. When a component is missing for a company, its weight is redistributed proportionally across the remaining components for that company so the weights still sum to 1.

4 · Integrity penalty & risk override

The risk component R is computed independently on a 0–100 scale where higher means more risk. It is inverted before entering the master formula as Sentiment Integrity:

SentimentIntegrity  =  0.10 · ( 100 − norm(R) )

R is built from:
  • Active controversies / litigation         (40%)
  • Greenwashing flags & NGO actions          (30%)
  • Regulatory scrutiny & enforcement signal  (20%)
  • Disclosure & transparency gaps            (10%)

Override. Companies with an active investigation have R locked at the higher of the model output or a manual override until the matter resolves — a strong score cannot mask an open enforcement action.

5 · CIP Grade · 1 to 5

The 0–100 C100 Score is mapped into a discrete CIP Grade. Grade 5 is the highest attainable grade and reserved for sector leaders.

Grade 5  ⇐  Score ≥ 85           Exceptional
Grade 4  ⇐  70 ≤ Score < 85       Strong
Grade 3  ⇐  55 ≤ Score < 70       Solid
Grade 2  ⇐  40 ≤ Score < 55       Developing
Grade 1  ⇐  Score < 40            Early

6 · Worked example

A reference C100 constituent with strong carbon activity, mid-tier credit-quality exposure, top-quartile ESG compliance, solid transition execution, deep financials, low risk, and moderate innovation:

norm(A) = 88     0.25 · 88        = 22.00
norm(Q) = 61     0.15 · 61        =  9.15
norm(E) = 82     0.20 · 82        = 16.40
norm(T) = 71     0.15 · 71        = 10.65
norm(F) = 74     0.10 · 74        =  7.40
norm(R) = 18     0.10 · (100−18)  =  8.20
norm(N) = 55     0.05 · 55        =  2.75
                                  ───────
                 C100 Score       = 76.55   →   Grade 4 · Strong

7 · Update cadence & governance

• Component inputs are refreshed on a rolling basis as registry data, filings, and news land.
• Scores recompute weekly; grade transitions require two consecutive weekly recomputes to take effect.
• The C100 constituent set is rebalanced quarterly from a Carbon Company Universe of 300–500 public companies.
• Methodology revisions are version-tagged and disclosed; cohort changes trigger a one-time backfill.
• Companies flagged with active investigations have their Risk component locked at the higher of the model output and a manual override until the matter is resolved.

8 · Related scoring models

The C100 Score is the flagship model. Adjacent universes use structurally similar formulas with sector-specific weights:

• Private Relevance Score — six-component model for private CDR suppliers, developers, MRV, marketplaces, and infrastructure.
• Transport Relevance Score — five-component model for public aviation and maritime constituents of the Public Carbon Universe.
• Sector Relevance Score — six-component model for Energy, Oil & Gas, Semiconductors, and Data Centers expansion candidates.
• See Methodology for the narrative overview and foundation layers (ICVCM, VCMI, Oxford Principles, IFRS S2, SBTi, CDP).