ESG Screening Framework Builder
Build defensible ESG screening frameworks with quantified pass/fail criteria and decision trees
What You Can Do
You'll create structured screening matrices with weighted criteria, threshold rules, and exclusion logic that systematically evaluate companies against your fund's ESG thesis. Build transparent decision trees that handle conflicting metrics, materiality variations, and geographic nuances—enabling you to evaluate 100+ candidates consistently while maintaining defensible audit trails for stakeholders, LPs, and regulators.
Features
Assign point values and thresholds to E, S, and G factors with customizable materiality weights per sector
Define hard stops (e.g., revenue % from weapons, fossil fuels) and soft flags (ESG rating below threshold) with override logic
Build tiered screening workflows (initial screening → deep dive → final approval) with pass/fail branching at each stage
Capture rationale for each criterion, data sources, and review frequency to satisfy compliance and LP reporting requirements
Model impact of changing thresholds (e.g., raising carbon intensity limits) on portfolio acceptance rate
Consolidate MSCI, Sustainalytics, Bloomberg, and custom research scores into one unified screening logic
Create reusable screening frameworks for consistent evaluation across multiple analysts and funds
Export decision logs showing which criteria each candidate passed/failed and why for regulatory documentation
Example Output
Example 1: Technology Sector Screening Matrix
- Company: TechCorp Inc.
- Environmental Score: 72/100 (Carbon intensity: ✓ Pass | Water risk: ✓ Pass | Waste management: ✗ Flag)
- Social Score: 65/100 (Labor practices: ✓ Pass | Supply chain: ✗ Fail due to audit findings)
- Governance Score: 78/100 (Board diversity: ✓ Pass | Executive pay ratio: ✓ Pass)
- Decision: FAIL — Social criteria below 70-point threshold; recommend exclusion unless supply chain audit remediated within 6 months
Example 2: Energy Sector Exclusion Logic
- Company: PowerGen Ltd.
- Revenue from thermal coal: 35% (exceeds 20% hard limit)
- Decision: AUTO-EXCLUDED — Fails initial fossil fuel revenue screen; no review required
Example 3: Threshold Impact Scenario
- Current framework: 150 of 500 screened candidates pass (30% acceptance rate)
- If carbon intensity threshold raised 15%: 187 candidates pass (37% acceptance rate)
- If board diversity requirement increased to 40%+ women: 118 candidates pass (24% acceptance rate)
What's Included
- SKILL.md instruction file with framework methodology and screening logic patterns:
- ESG Screening Matrix Template: Pre-built weighting structure for E, S, G factors with sector-specific materiality guidance
- Exclusion Rules Checklist: Common hard stops and soft flags (fossil fuel revenue %, controversy thresholds, governance red flags)
- Multi-Stage Decision Tree Workflow: Tiered screening process from initial filter through final approval with pass/fail branching
- Threshold Documentation Framework: Structure for capturing criterion rationale, data sources, and review frequency for compliance audits
Who It's For
- ESG/Impact Investment Analysts — evaluating companies against fund mandates
- Portfolio Managers — building systematic exclusion and inclusion policies for regulated portfolios
- Compliance & Risk Officers — documenting screening logic for LP reporting and regulatory reviews
- Fund Operations Teams — standardizing ESG evaluation across multiple analysts or fund strategies
- Institutional Investors — constructing custom screening criteria aligned with impact theses
Best For
- Building new ESG screening policies or updating existing investment frameworks
- Evaluating portfolios of 50+ companies with complex, mixed ESG profiles
- Creating defensible audit trails and decision documentation for regulated funds
- Integrating multiple ESG data sources (MSCI, Sustainalytics, Bloomberg) into unified screening logic
- Standardizing screening decisions across teams to eliminate analyst bias and inconsistency
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