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Our Process

The average large-cap fund manager holds 13% of their index. Divestment is the defining property of active management — not a practice unique to ethical investors.

The question is never whether to exclude — it's which companies, and why.

Three goals:

  • Avoid preventable harm
  • Seek available goodness
  • Know the difference

Conduct Screening as Risk Management

Misconduct moves the market. Within five days of reported corporate misconduct, the average stock is down 4.1%. Environmental violations (-9.2%) and accounting fraud (-8.32%) produce even sharper reactions.1

Professional investors correctly identify financial deception 39% of the time — below chance.2 This compromises the SEC filings, official statements, and financial models we traditionally use to assess companies.

Screening is both a moral imperative and a preemptive defense: removing companies from our universe helps us concentrate on our best opportunities and avoid the positions where that blindspot causes the most damage.

  1. Ichev, R. (2023). Reported corporate misconducts: The impact on the financial markets. PLoS ONE, 18(2), e0276637. doi:10.1371/journal.pone.0276637
  2. Hartwig, M., Voss, J. A., Brimbal, L., & Wallace, D. B. (2017). Investment professionals' ability to detect deception: Accuracy, bias and metacognitive realism. Journal of Behavioral Finance, 18(1), 1–13. doi:10.1080/15427560.2017.1276069

1. Avoid Preventable Harm

Screening, Divestment & Exclusions

Our screening framework divides into two types, each addressing a distinct form of risk.

Ethical Screening

Product-Based Exclusions

What companies make and sell — categorical rejections of harmful business lines.

2.1 Harm to Living Beings
  • Meat, dairy, eggs, honey, butter, silk, cheese
  • Leathers, hides, furs, and exotic skins
  • Equipment that directly harms animals
  • Animal testing for commercial products
  • Industrial-scale confined animal feeding
  • Animal entertainment (racing, captive display)
2.2 Weapons and Military Systems
  • Weapons, military materiel, and defense consulting
  • Defense equipment and technologies
  • Nuclear weapons production
  • Retail firearms sales and promotion
2.3 Addictive and Harmful Products
  • Tobacco and nicotine products
  • Gambling operations and platforms
  • Alcohol production and distribution
  • Opioid manufacturing and distribution
  • Pesticide and toxic chemical manufacturing
  • Exploitative entertainment business models
2.4 Fossil Fuels and Extractive Industries
  • Upstream: oil, gas, and coal exploration and production
  • Midstream: pipelines, storage, LNG facilities
  • Downstream: refining, processing, and retail
  • Oilfield services and equipment
  • Mining and extractive industries
2.5 Surveillance Technology
  • Surveillance hardware (cameras, sensors, screening)
  • Intelligence and forensic software
  • Surveillance infrastructure for governments or corporations

Conduct-Based Exclusions

How companies behave — corporate actions and patterns of harm from operational choices.

3.1 Forced Labor, Child Labor, and Trafficking
  • Coerced labor and modern slavery
  • Child labor in operations or supply chains
3.2 Worker Rights and Workplace Safety
  • Anti-union activity and suppression of collective bargaining
  • Workplace discrimination (age, race, gender, disability)
  • Unsafe working conditions and preventable injuries
  • Wage theft and contractor misclassification
  • Deaths attributable to corporate negligence
3.3 Conflict, Occupation, and Indigenous Rights
  • Complicity in armed conflict or military occupation
  • Operations in or support of occupied territories
  • Violations of indigenous community rights
3.4 Environmental and Climate Misconduct
  • Pollution, contamination, and ecological destruction
  • Greenhouse gas emissions and air quality violations
  • Failure to develop credible climate transition plans
  • Waste management failures and plastic pollution
  • Water contamination and excessive extraction
3.5 Financial Crime and Market Abuse
  • Securities fraud, accounting fraud, market manipulation
  • Bribery, FCPA violations, and gross corruption
  • Aggressive tax avoidance schemes
  • Antitrust violations and price fixing
3.6 Consumer and Community Harm
  • Predatory lending and extractive financial products
  • Consumer protection failures and deceptive practices
  • Externalized costs to communities
  • Abuse of legal systems (patent trolling, litigation as business model)
3.7 Political Influence and Democratic Integrity
  • Corporate resources used to influence political outcomes
  • Dark money contributions and undisclosed spending
  • Financial support for politicians restricting essential services
3.8 Information Integrity and Platform Accountability
  • Disinformation, greenwashing, and consumer deception
  • Operating or financing for-profit incarceration
  • Surveillance capitalism against own users
3.9 Regulatory and Governance Failures
  • Systemic compliance failures and regulatory violation patterns
  • Failure to provide appropriate oversight

See an example: ExxonMobil (XOM) →

2. Seek Available Goodness

Company Analysis

We're looking for companies that generate positive impact the same way they generate revenue.

This is hard. Most companies do some good and some bad, and the good is often incidental to the business model. We want the subset with a money-making mechanism that also manifests positive change.

What does structural alignment select for?

  • Companies with deep install bases, recurring revenue, and high switching costs.
  • Products worth more than they cost.
  • Businesses you can see existing a hundred years from now doing more or less the same thing.

The ethical filter naturally selects for durability, because businesses built on extracting value from people or the planet have a shelf life.

Decision Drivers

Key questions we ask

1
Who works there?
  • Leadership quality and tenure
  • Culture red flags, high turnover
  • Stakeholder treatment track record
2
What do they sell?
  • Product differentiation and pricing power
  • Stagnant product lines, commoditization risk
  • Innovation pipeline depth
3
Can they keep making it?
  • Operational efficiency and execution
  • Supply chain integrity
  • Track record of delivery
4
Do they make money making it?
  • Cash flow quality and consistency
  • Margin trajectory
  • Balance sheet strength
5
Who else could make it?
  • Moat depth and switching costs
  • Competitive differentiation
  • Barriers to entry
6
What could stop them?
  • Regulatory exposure
  • Litigation and liability risk
  • Systemic vulnerabilities

The Research Infrastructure

Built to accumulate wisdom, not just data.

An Independent AI Colleague

The CIO makes every investment decision. The AI doesn't pick stocks — it decides which of the stocks in our pipeline need the CIO's attention today. It pulls SEC filings, earnings call transcripts, and web sources; cross-references against our full research library via semantic search; and produces independent assessments.

The CIO scores conviction on every company. The AI scores conviction independently. When they disagree, the company gets flagged for deeper work. This isn't automation replacing judgment — it's a second opinion that never forgets anything we've learned.

The Quality Gate

Deterministic Checks
AI Quality Review
CIO
AI
Independent Conviction Scoring
Disagreements Flagged

3. Know the Difference

Decision Refinement & Learning

“This process is an expression of hope in the face of experience.”

— Sloane Ortel, Founder & CIO

It is very hard to make good investment decisions.

It is even harder to make good investment decisions that are also good ethical decisions. We are wrong sometimes. We evaluate this process by how well we accumulate knowledge over the long term, not by pretending we got everything right the first time.

Companies find new and exciting ways of disappointing us all the time. Maybe they announce a new business line that conflicts with your values. Maybe a leadership change shifts priorities. Maybe an earnings call reveals something the research note didn't anticipate. The question isn't whether this happens — it's what you do when it does.

The screening policy isn't a rulebook handed down once. It began as a derivative of Norges Bank's framework — institutional, deliberative, built for a sovereign wealth fund. We kept the taxonomy and dropped the bureaucracy. The principles stayed broad by design: broad enough to hold when reality presents a case the rules don't anticipate.

Version 4 of our taxonomy introduced 57 sub-categories across 12 themes, enabling AI-assisted classification where two applications of the same principle produce the same result. Making the reasoning reproducible turns out to also make it auditable.

The research compounds. Every revised note is a lesson recorded. Every disagreement between the CIO's conviction score and the AI's flags something worth examining. Over time the library accumulates not just data but judgment — what we thought, when, and why, cross-referenced against everything since.

Veil-of-Ignorance Reasoning

Derived from philosopher John Rawls

When a situation doesn't fit neatly, the question is Rawls's: how would we feel about this outcome without knowing which party we'd be?

Shareholder Employee Community Member Person Downstream The Animal The Ecosystem

Research consistently shows this approach produces decisions that favor the greater good.3

  1. Huang, K., Greene, J. D., & Bazerman, M. (2019). Veil-of-ignorance reasoning favors the greater good. Proceedings of the National Academy of Sciences, 116(48), 23989–23995. doi:10.1073/pnas.1910125116 PMID: 31719198.

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Investment strategies involve risk of loss. Past performance does not guarantee future results. Ethical screening removes investment candidates and produces sector exposures that differ materially from unscreened benchmarks — affecting performance in both directions. The Growth strategy is concentrated and will diverge significantly from broad market indices.