2026 Guide | AI in Financial Services

Stop Screening Blind. Start Screening Smart.

Clarity, Control, and Confidence in Every Screen

Apply tailored exclusion criteria with detailed, revenue-based data, so you can align investments with values, mandates, and risk tolerance.

Trusted by Leading Financial Institutions

The Challenge Isn’t Screening, It’s Doing It Right

Negative screening is one of the most established ESG practices, but executing it at scale is another story. Assessing indirect exposure, handling undisclosed revenues, and applying consistent criteria across thousands of companies requires reliable, transparent data. Without it, exclusions can become inconsistent, time-consuming, and difficult to defend.

Our Solution, at a Glance

Clear, Customizable, Credible Exposures

Apply Exclusions Across a Broad, Detailed Universe

Designed to support exclusion policies across industries and themes:

  • 45,000+ companies across sectors and geographies
  • 19 categories and 55 sub-topics for more precise screening
  • Captures both direct and indirect involvement

Remove Ambiguity with Granular Data

Built to reduce false positives and avoid unnecessary exclusions:

  • Exact or best estimate percentage of a company’s involvement in controversial activities
  • Revenue data at sub-topic level for higher accuracy
  • Custom thresholds to define exposure relevance

Back Every Decision With Verifiable Evidence

Structured to make your exclusions traceable and explainable:

  • Access to source documents like reports and company websites
  • Visibility into estimation methodology when applied
  • Clear documentation to support internal and external reporting
EU ESG Ratings Regulation

Clarity AI, a Leading Voice in Shaping the Regulation

What We Stand For

AI You Can Rely On. Data You Can Defend.

AI That Powers Smart, Scalable Screening

AI helps you go deeper, and faster. Our models extract and analyze structured and unstructured data to identify company involvement across sensitive activities using NLP and LLMs to surface exposures others might miss. This lets you move beyond simple classifications and apply exclusion policies with more precision, context, and confidence.

Data That Holds Up to Scrutiny

In exposure screening, trust starts with transparency. Every data point in our platform is standardized, validated, and fully documented. So, you can understand what’s behind each flag, justify every exclusion, and communicate decisions clearly to clients, boards, or regulators.

Beyond ESG Risk

Enhance Your Sustainability Risk Analysis Even Further

ESG Scores

Choose scores aligned to global standards or tailor them to your own ESG strategy, with every input traceable, explainable, and ready for review.

UN SDGs

Assess portfolio alignment with the Sustainable Development Goals (SDGs) using science-based, granular data. Built for flexibility, transparency, and impactful reporting.

ESMA Naming Rules

Avoid costly exclusions and compliance doubts with data that’s clear, precise, and built to stand up to scrutiny.

Screening That Fits Every Workflow

Implement Exclusions With Confidence

Clarity AI helps asset managers apply exclusion policies across portfolios with transparent, data-driven exposure insights. Granular revenue data and flexible thresholds enable more informed decisions without over-screening or sacrificing alignment with investment mandates.

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Monitor and Enforce Screening Policies at Scale

Asset owners can evaluate portfolio exposure to controversial sectors and track direct and indirect involvement with precision. With standardized, revenue-based insights, it’s easier to stay aligned with sustainability commitments and manage reputational and financial risk.

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Support Client Preferences With Clear, Defensible Data

Clarity AI helps wealth managers report on exposure to restricted sectors with full transparency. With granular insights, they can align portfolios with client values, ensure ethical standards, and meet screening requirements without overcomplication.

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Strengthen Risk Management Across Portfolios

Banks can assess company involvement in restricted activities and align investment and lending decisions with internal policies and regulatory requirements. Granular exposure insights bring transparency and consistency to ESG risk assessments.

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FAQs

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  • What insights does the Exposures solution provide?

    Clarity AI provides revenue-based data on company involvement in 15 categories and 47 sub-topics such as fossil fuels, defense, alcohol, and tobacco. This helps investors align portfolios with exclusion policies, values, and regulatory requirements.

  • Where does the exposures data come from?

    Our team collects data from annual reports, regulatory filings, company websites, NGOs, media search tools, and business directories. We also use AI-driven methods like large language models (LLMs) to enhance coverage and reliability.

  • How much of the data is estimated?

    Many companies don’t report the data needed for business involvement screening. We provide full transparency by clearly indicating whether each data point is reported or estimated. Reported data includes the source and a direct link to the evidence. For estimated data, we offer links to supporting sources and a clear explanation of the estimation methodology.

  • Can I use Exposures data in a broader mandate?

    Yes, the data is accessible through our web app and via APIs and data feeds, making it easy to combine it with other datasets for more in-depth screening within your existing workflows.

  • How does Clarity AI handle direct vs. indirect exposure?

    We distinguish between companies directly generating revenue from a flagged activity and those indirectly involved through ownership or supply chains. This level of granularity helps avoid over-exclusion and supports more precise screening aligned with your investment policies.

Research and Insights

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June is a month when corporate communications are filled with Pride messaging, diversity commitments, and inclusion statements. But beyond the visibility of these declarations, a more complex question remains: do these commitments consistently align with companies’ actual conduct? At Clarity AI, we looked at whether companies with active discrimination controversies in practice also publicly emphasize…

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The physical risk gap: What today’s datasets are missing

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