ESG isn't just about compliance; it's about material risk. Move beyond opaque "Black Box" ratings. Access raw, audit-grade sustainability data—from Scope 3 Carbon Emissions to Board Diversity ratios—mapped directly to global regulatory frameworks like SFDR, TCFD, and SASB.
Raw Data. No Greenwashing. Most providers give you a subjective letter grade (e.g., "A-"). We give you the raw numbers that drive the score, allowing you to build your own materiality models.
Why does one agency rate Tesla an "A" and another an "F"? Because their weightings differ. We provide the Raw Underlying Metrics (e.g., "Total Water Withdrawal," "CEO-to-Median Pay Ratio") so you can apply your weightings and methodology, not ours.
Direct emissions (Scope 1) are easy. The risk lies in the supply chain (Scope 3). Our machine-learning models estimate upstream and downstream emissions for 50,000 companies, exposing hidden carbon liabilities in your portfolio before regulators do.
Annual sustainability reports are backward-looking. Our Controversy Engine scans 100,000+ news sources daily to flag real-time governance risks—labor strikes, data breaches, or executive fraud—giving you a "Governance Signal" that moves faster than the 10-K.
Get me the exact Carbon Intensity per $1M Revenue for XOM.
Download the full ESG universe to screen for SFDR Article 8/9 compliance.
Query the sustainability report: "What is the company's specific target year for Net Zero?"
Sync our ESG_Master table to your warehouse for automated portfolio scoring.
{
"ticker": "TSLA",
"period": "2024",
"esg_score_aggregate": 68.5,
"Environment": {
"scope_1_emissions": 210500,
"scope_2_emissions": 450000,
"scope_3_estimated": 12500000,
"carbon_intensity": 45.2,
"net_zero_target": 2040
},
"Social": {
"employee_turnover": 0.18,
"gender_pay_gap": 0.02,
"lost_time_injury_rate": 1.4
},
"Governance": {
"board_independence": 0.65,
"dual_class_share": false,
"controversy_flag": "High (Labor)"
}
} scope_3_estimated The biggest data gap in the market. We use sector-specific input-output models to estimate these supply chain emissions when companies fail to report them. carbon_intensity A normalized metric (Tonnes CO2e / $1M Revenue). This allows you to fairly compare the carbon efficiency of a massive conglomerate against a small cap peer. controversy_flag A real-time signal derived from news sentiment. A "High" flag indicates active litigation or reputational damage (e.g., a massive recall or labor dispute) that hasn't hit the annual report yet. board_independence A key governance proxy. Research shows that boards with >75% independent directors correlate with lower volatility and better long-term capital allocation.
Our team of experienced financial advisors is here to provide personalized guidance and support.
We scrape Annual Sustainability Reports, CSR filings, 10-Ks, and Proxy Statements. For missing data points (common in Emerging Markets), we use proprietary estimation models based on peer groups and revenue mix.
Yes. Our taxonomy is built to map directly to the SASB Materiality Map and TCFD disclosure recommendations. We also tag data points required for EU SFDR PAI (Principal Adverse Impact) reporting.
Daily. While the core "metrics" (like Emissions) are annual, the "Risk/Controversy" score is updated every 24 hours based on news flow, regulatory fines, and legal filings.
Yes. Via our Vector API, you can retrieve the exact paragraph in the PDF where the company claimed their "Net Zero" target, allowing for effortless auditing and greenwashing checks.
ESG metrics are frequently restated as companies improve their measurement methodologies (e.g., re-calculating 2020 emissions using a new 2022 protocol). We strictly maintain a Point-in-Time database. If you request data for 2020, you get the number exactly as it was reported in 2020, ensuring your backtests don't suffer from look-ahead bias caused by retroactive data cleaning.
Yes. For EU-based asset managers, we have a dedicated compliance_sfdr endpoint. This maps our raw metrics directly to the mandatory Principal Adverse Impact (PAI) indicators required for Article 8 and Article 9 funds, such as "Exposure to Controversial Weapons" and "Unadjusted Gender Pay Gap," streamlining your regulatory reporting.
