Client Success Story

ESG Exposure Research Services at Scale: Controversial Activity Screening for 3,000+ Companies

95%+

QA First
Pass Rate

10+

Exposure Categories
Covered

Service

Platforms

  • Client's Proprietary ESG Rating Platform
The client

A Mid-Market EU ESG Ratings and Data Provider Expanding Exposure Coverage

The client is an exposure metrics data vendor for asset managers, banks, and sustainability-focused investors across the region. Their datasets sit alongside broader ESG screening services in client workflows, used to apply environmental, social, and ethical risk thresholds against held or prospective portfolio companies. They maintain a proprietary ESG rating platform where analysts publish company-level ESG data on disclosed business activities, revenue contribution, and exposure classifications.

CLIENT OBJECTIVE

Set up a Traceable Exposure/Controversy Screening Data Feed

The provider's exposure dataset was designed as a quantitative, source-traceable feed that estimates each covered company's revenue-based exposure to specific controversial business activities. Unlike topical ESG data research — where qualitative assessment and broad sector classification often suffice — exposure data sits at the activity level, and every estimate had to be backed by disclosed evidence, financial filings, or a defensible revenue-based exposure proxy. The provider needed a partner who could absorb their proprietary methodology, work with their evolving SOPs, and progressively scale coverage across the controversial activity universe.

PROJECT REQUIREMENTS

ESG Exposure Research Services with Related Revenue Estimation across 10+ Metrics, 3000+ Companies

The scope of work covered end-to-end exposure metrics data collection — from methodology adoption to evidence sourcing, revenue calculation, and platform delivery.

  • Methodology adoption: Internalize the provider's hierarchical Metric → Activity → Evidence → Revenue workflow and align to their evolving SOPs.
  • Evidence sourcing: Pull and triangulate ESG disclosure data from corporate filings, official company portfolios, and product/service catalogs. For some activities — gambling, cannabis-adjacent products, certain defense exports — the same business line counts as exposure in some jurisdictions but not in others, so sector and geographic exposure data had to be captured against each activity record.
  • Revenue estimation: Calculate exposure percentages using either disclosed segment revenue or defensible asset-based and product-based proxies.
  • SOP versioning: Track and adopt every change to the client's SOPs without breaking throughput or audit trail.
  • Platform integration: Publish completed records directly into the Client's Proprietary ESG Rating Platform for downstream use as due diligence data feeds in client workflows.
Exposure Metrics Research: Coverage Scope
Oil-Sands Production & Participation Animal Testing & Animal Cruelty
Arctic Oil and Gas Contraceptives and Abortifacients
Coal Mining Production & Participation Adult Entertainment Industry
Fossil Fuels & Related Energy Gambling & Leisure Industry
Conventional Weapons Production & Participation Alcohol and Other Drugs
Nuclear Energy
PROJECT CHALLENGES

Granular Exposure Research Methodology and SOPs that Kept Evolving Mid-Engagement

  • A Methodology Unfamiliar Even to Experienced ESG Analysts

    The obstacle here was not a lack of ESG experience — our analysts had 5+ years of experience across adjacent ESG datasets — but the fact that Exposure ESG operates fundamentally differently. Standard ESG ratings ask "how does this company perform on a topic?" and reward qualitative judgment. Exposure ESG asks "what share of this company's revenue comes from a specific business activity?" and rejects qualitative judgment in favor of disclosed evidence and traceable arithmetic.

  • SOPs that were Updated Multiple Times through the Project

    The client's methodology and standard operating procedures were not static. As they refined how exposure should be calculated for edge cases — REITs with mixed property portfolios, conglomerates with minor exposed segments, companies relying on asset-based proxy calculations — the SOPs were revised multiple times during the engagement. Each update meant the team had to absorb new rules, back-test their effects on already completed records, and stay aligned with the client's research leads without losing weekly throughput.

  • Scaling Coverage without Compromising Methodological Rigor

    The engagement began as a 3-month proof-of-concept with a 5-analyst team. Once the methodology was validated, the client expanded the scope rapidly — both the number of companies under coverage and the breadth of exposure categories handled. Scaling the team without quality drift required structured onboarding, peer review at multiple levels, and tight version control (on which SOP each analyst was working at any given time) — effectively, activity-based risk profiling at production scale.

  • Triangulating Defensible Revenue Estimates for Niche Activities

    Many of the controversial activities under review were not reported separately in standard financial filings. Alcohol sold on an airline, casino revenue inside a hospitality REIT, contraceptive revenue inside a diversified pharmaceutical company — none of these typically appeared as standalone line items. Analysts built revenue estimates from multiple inputs: company websites, official menus and portfolios, segment disclosures, and asset-based proxies — for instance, the share of gaming-related properties in a REIT's portfolio. Every estimate had to be sourceable, reproducible, and conservative.
OUR SOLUTION

A Methodology-First Research Workflow, Phased Scaling, and Layered QA

For this ESG exposure research project, we focused on a single operating principle: master the methodology first, then scale. Our analysts ensured disciplined application of the client’s documented methodology, including category-level defaults and version-tracked SOPs, across thousands of records and a growing analyst pool.

1

A 3-Month POC with a Dedicated 5-Analyst Pilot Team

We began the engagement as a structured 3-month proof of concept in June 2025. A dedicated team of 5 ESG analysts — selected from our broader research bench for their depth in disclosure-based research — was assigned full-time to absorb the client's methodology. The POC scope was deliberately narrow:

  • Cover a defined set of companies across a subset of exposure metrics
  • Validate the workflow end-to-end, and surface any methodological ambiguities before scaling

By the close of the POC, the team had built internal reference material, working files for each exposure category, and a clear handover protocol between research and quality review.

2

Version-Tracked Methodology Adoption with Peer-Reviewed SOP Updates

To manage the client's evolving SOPs, we ran the engagement using a version-tracking methodology. Every SOP update was logged, peer-reviewed within the team, and walked through with the client's research leads in alignment sessions before being rolled into active research.

SOP changes were not cosmetic — they typically redefined how exposure was calculated for a specific activity class. Our protocol was to identify the records in scope of each change, re-run them under the new SOP, and reconcile the deltas. Records not affected by the change were left as is. This kept the audit trail clean — every record could be tied to the SOP version under which it was produced — and prevented the team from working off stale guidance.

3

A Standardized Workflow to Analyze Metrics, Activities, Evidence, and Revenue

We operationalized the client's hierarchical model as a repeatable analyst protocol grounded in business involvement screening and product involvement screening principles. For each company, an analyst carried out the following:

  • Ran AI-assisted screening using research tools (ChatGPT, Perplexity, Claude, Gemini) to point analysts toward where exposure evidence was likely to sit across disclosures, filings, and reports.
  • Verified every AI-generated and manually-sourced lead against a primary source before it entered the dataset — confirming the cited document, filing, or page actually existed and was accessible. Leads that passed entered the active research queue; leads that could not be verified were discarded and logged in the audit trail as unverified, building a running record of AI reliability over time.
  • Mapped disclosed business activities to the client's mutually exclusive activity codes — for example, distinguishing oil exploration from refining from distribution, and separating direct Production from indirect Participation on every metric.
  • Traced exposure through complex corporate structures where present — following subsidiaries, joint ventures, and equity stakes so that involvement held below the parent level was captured rather than missed.
  • Attached at least one primary evidence source to every classified data point — for a complete, line-by-line audit trail traceable to the source document, page, and date.
4

Multi-Source Evidence Triangulation for Exposure Calculations

Our team moved beyond pure qualitative exposure research into source-traceable quantitative estimates. To calculate the exposure percentages, we used actual data on disclosed segment-wise business revenue when available. When that data wasn't available, we used reliable estimates rather than guessing, ensuring the final numbers were fully traceable to their sources.

When a company reported ancillary revenue as a bundled line item — for instance, an airline's bundled passenger revenue that includes on-board alcohol sales — analysts applied a documented estimation method, capped at a conservative percentage and explicitly labeled as an estimate. For asset-based exposures common in REITs and holding companies, analysts calculated the share of exposed assets in the portfolio and applied that ratio to the corresponding revenue stream. Every calculation included its formula in the working file so the client's review team could trace the math end-to-end.

5

Tiered Peer & Senior Quality Review at Production Scale

A two-tier QA layer sat on top of the research workflow. Peer review caught classification slips and missed evidence sources; senior review checked methodology compliance, revenue formula integrity, and edge-case handling against the latest SOP version. The two-tier model maintained a QA pass rate of 95%+ as the team scaled from 5 to 13 analysts and coverage expanded to thousands of companies.

6

Phased Team Expansion Mapped to Coverage Growth

As the client's confidence in the workflow grew and coverage targets expanded, we scaled the team in phases — adding analysts in small batches, with each batch absorbing the methodology under a structured onboarding plan led by senior team members. Over 10+ months, the team grew from 5 to 13 analysts while sustaining per-analyst throughput of 100+ companies per month.

WORKED EXAMPLE

Alcohol Participation Examination for a US-based Passenger Airline

For this ESG exposure research project, we focused on a single operating principle: master the methodology first, then scale. Our analysts ensured disciplined application of the client’s documented methodology, including category-level defaults and version-tracked SOPs, across thousands of records and a growing analyst pool.

01
Metric Identification

Metric Identification

An analyst opens the airline industry checklist and flags "Alcohol" as a relevant metric group, since passenger carriers commonly serve alcoholic beverages on board.

02
Activity Mapping

Activity Mapping

Within the Alcohol metric group, the analyst maps the evidence to exp_alcohol_participation (the activity code for direct retail of alcoholic beverages to consumers).

03
Evidence Sourcing

Evidence Sourcing

Data is captured from three sources:

  • The airline's official Main Cabin menu listing beer, wine, spirits, and canned cocktails for sale
  • The Premium Class fare description confirming complimentary alcoholic drinks
  • The 10-K passenger-revenue note confirming that on-board food and beverage sales are reported as part of bundled passenger revenue and not broken out as a separate line item

Each source link is logged for downstream audit.

04
Revenue Calculation

Revenue Calculation

Because the airline does not break out alcohol sales as a standalone line item (as deduced from the 10-K), the analyst applies the documented estimation rule for bundled ancillary revenue: a conservative percentage assumption (0.01% of total passenger revenue), explicitly labeled as an estimate in the record. Against ~$14.2B in reported revenue, this produced an exposure revenue figure of ~$1.42M and an exposure percentage of 0.01%.

05
Handoff

Handoff

The completed record — with activity coed, three evidence links, formula, and final percentages — is passed through peer review, then senior review, and finally published on the client's platform.

Project Outcomes

The engagement validated our ESG exposure data collection services as a scalable model for ratings providers and ESG data research firms building activity-level ESG risk exposure data.

Companies Under Exposure Coverage

3,000+ Companies Under Exposure Coverage Providing our client with a research-grade, activity-based ESG data feed broad enough to support their institutional screening clients with comprehensive exclusion lists.

QA Pass Rate

95%+ QA Pass Rate across the Exposure Dataset Sustained even as the coverage universe scaled, enabling the client's research team to focus its attention on edge cases rather than routine corrections.

10+ Exposure Categories in Production

10+ Exposure Categories in Production Fossil fuels, alcohol, gambling, animal testing, and other controversial activity domains and aligned with the client’s institutional exclusion frameworks.

Team Scaled

Team Scaled from 5 to 13 Analysts in 10+ Months Growing capacity alongside the client's coverage targets and without measurable drift in QA pass rates or per-analyst throughput.

Going from five to thirteen analysts on a methodology this granular is where most ESG outsourcing engagements quietly degrade because new resources default to general ESG instincts and miss the activity-level discipline. We paired every new analyst with a senior reviewer for their first batch of records to tackle that very issue, and the data quality held because that bar of acceptable quality was never compromised.

— Kuldeep Kumar (Project Manager, SunTec India) | linkedin-icon

CONTACT US

Scale Your ESG Exposure Research with SunTec India

This engagement is one of a growing portfolio of ESG exposure research services we deliver to ratings providers, data vendors, and sustainability-focused asset managers. Our broader ESG data research and collection services — covering controversial activity screening, sustainability data management, norms-based research and screening, due diligence data feeds, and company-level ESG data collection across multiple frameworks — are built around the same operating model: dedicated research teams, version-tracked data collection & processing, and tiered QA at production scale.

If you are building an exposure dataset, expanding coverage of an existing one, or scaling an in-house ESG research function, request a free sample of our ESG exposure research services.