The concept layer.
Canonical definitions for the vocabulary autonomous finance is being built in — each with a defined meaning and, more usefully, a position on why it matters that a definition alone cannot carry. The glossary fixes terms. This fixes arguments.
The twelve.
Chosen where the intersection of systematic finance and agentic infrastructure is real and the existing writing is thin. Where a term already has a settled definition elsewhere, we defer to it and argue about the consequences instead.
The degradation of a model's predictive relationship with its target over time, as the data-generating process moves away from the conditions the model was fitted under. Distinguished from data drift, where inputs shift but the underlying relationship does not.
The property that a dataset reflects only information genuinely available at each historical timestamp — including the values as first reported, before restatement, and the constituent sets as they stood, before survivorship filtering.
Pre-committed, quantified conditions under which an automated strategy or agent is halted without further discretionary judgement — specified before deployment and binding on the operator.
The verifiable record of what a model is: training data and its licence terms, base model lineage, fine-tuning corpus, versioned weights or endpoint identity, and the transformations applied between raw data and deployed artefact.
The unbroken record of ownership and licence rights running from every input used to build a model through to the model's outputs — the analogue of chain of title in real property, or clearance in music and film.
The persistence layer through which an autonomous agent carries state across invocations — working context, retrieved documents, prior decisions, and learned preferences — distinct from the model weights themselves.
The chain that turns a query into model context — chunking, embedding, indexing, retrieval, reranking and assembly — determining what evidence a model sees before it produces an answer.
Retrieval-augmented generation over a knowledge graph rather than a flat vector index, using typed entities and explicit relationships so that retrieval can traverse connections rather than only match similarity.
Formal specifications of financial concepts and their relationships — instruments, entities, events, exposures — with defined semantics that permit machine reasoning rather than only machine reading.
The set of controls under which a system may take consequential action without prior human authorisation for each act — covering the authority grant, its bounds, the oversight interval, and the conditions of revocation.
Artificially generated data that preserves selected statistical properties of real data — used for augmenting sparse regimes, stress testing, and working around licensing or privacy constraints on the original.
The property that a stated result can be regenerated exactly from published inputs and procedure — same data as of the same moment, same code version, same parameters, same output.
Definition and position.
Every page here separates two things that are usually blended. The definition is intended to be uncontroversial — if you disagree with it, we have probably made an error and would like to know. The position is a claim, argued, and you are welcome to disagree with it in public.
Keeping them apart is what makes the definitions citable by people who reject the positions, which is the more useful outcome.