rgets: a commitment to exit any type of fossil fuel financing, including commitments to exit with residual exposure, is in scope, but a target to cut financing or financed emissions without an exit is not. This is true even if such targets represent interim milestones within an exit strategy. ### Commitment fields For each commitment, we extract a defined set of fields that determine its scope and strength. This standardizes the explicit and implicit applicability rules that most commonly determine a policy's breadth and effectiveness. | Structured fields | What they capture | | :---------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Sector |

Theme: coal or oil & gas
Sub-type: thermal or metallurgical coal; shale, oil sands, etc.
Value chain: upstream, midstream, or downstream
Asset stage: new and/or existing assets

| | Geography |

Scope: global or limited to named regions or countries

| | Counterparty |

Entity: borrower or group (including parent and subsidiaries)
Relationship stage: new and/or existing clients

| | Product |

Financing type: project finance or corporate finance
Capital markets: facilitation included or not
Transaction stage: new and/or existing transactions (e.g., refinancing)

| | Timing |

Effective date: immediate or deferred

| **Triggers** Commitments to not fund fossil fuels are often based on threshold values defining what constitutes a fossil fuel company or project. To capture this, we record a number of composite fields: - quantitative triggers: numeric inequalities specifying a threshold (\>25% of revenue from coal) - qualitative triggers: written descriptions of the threshold (“‘significant’ revenue from coal”) - timeframe: when a measurement is specified to be taken (“revenues based on the most recent fiscal year”) **Loopholes** Carve-outs to commitments often prove too varied to standardise. As a result, we also capture a less-standardized “loophole” field with two subfields - Exceptions: a list of written exceptions to the policy - Weaknesses: descriptions of how loopholes might undermine a policy’s effectiveness. Keeping loopholes separate from the structured dimensions reflects a deliberate choice: the dimensions standardise the limits that recur across banks, while loopholes capture bespoke conditions that otherwise would not fit a fixed field. ## Synthesis & verification process On a high level, the process of cataloging commitments is very similar to how linguists diagram sentence structure, but applied to a text as a whole. While there is ambiguity in commitments, as there often is in language, there is still useful information to be extracted and synthesised. Policy synthesis is derived using the above fields and large language models (LLMs, often known as chatbots) in a multiple-pass processing pipeline. We verify the accuracy of our processing pipeline by comparing its results to a ground-truth set of syntheses derived by human analysts. This ground-truth dataset covers a range of bank fossil fuel exclusion policies, ranging from simple to extremely complica