Definition · AI in finance
Hallucination
Hallucination is a model producing plausible but fabricated or incorrect output. For hallucination, the useful boundary is the data it uses, the tools it can call, the approvals it needs, the review standard, and the finance decision it may influence before the output is trusted or automated.
Also known as AI hallucination, LLM hallucination
Why it matters
Understanding hallucination matters because AI-assisted finance work can sound confident even when data, assumptions, or compute paths are wrong. A useful definition keeps the output grounded, reviewable, and accountable. Pluvo computes every number with a deterministic engine and traces it to source, so figures are never fabricated the way a freeform LLM answer can be.
In practice
Governance example
Teams use hallucination when they evaluate whether an AI-assisted analysis can be trusted. The useful test is whether the output is tied to approved data, repeatable logic, human review, and an audit trail.
Pluvo example
Pluvo computes every number with a deterministic engine and traces it to source, so figures are never fabricated the way a freeform LLM answer can be.
In practice, teams should define hallucination with a clear source, owner, time period, and decision before they use it in reporting, planning, or operating reviews.
Understanding hallucination matters because AI-assisted finance work can sound confident even when data, assumptions, or compute paths are wrong. A useful definition keeps the output grounded, reviewable, and accountable. Pluvo computes every number with a deterministic engine and traces it to source, so figures are never fabricated the way a freeform LLM answer can be.
A strong workflow for hallucination separates the definition from the action: first agree what the term means, then decide how it is measured, when it changes, and who is accountable for the next step.
Pluvo computes every number with a deterministic engine and traces it to source, so figures are never fabricated the way a freeform LLM answer can be.
FAQ
What is an AI hallucination?
Hallucination is a model producing plausible but fabricated or incorrect output. For hallucination, the useful boundary is the data it uses, the tools it can call, the approvals it needs, the review standard, and the finance decision it may influence before the output is trusted or automated.
Why do LLMs hallucinate?
Understanding hallucination matters because AI-assisted finance work can sound confident even when data, assumptions, or compute paths are wrong. A useful definition keeps the output grounded, reviewable, and accountable. Pluvo computes every number with a deterministic engine and traces it to source, so figures are never fabricated the way a freeform LLM answer can be.