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FinanceGPT

QUANTITATIVE GOVERNANCE

Show how a financial output became an approved decision.

A financial institution must be able to explain its own use of AI-generated work. FinanceGPT focuses on the evidence, quantitative evaluation, permissions and review records around that use.

Start free. Upgrade when the work needs retained evidence, review controls and a shared paid workspace.

A GOVERNED FINANCE WORKFLOW

From AI output to a decision your institution can use.

01

Check the work

Bring the financial output, sources and assumptions together.

02

Evaluate the model

Inspect the relevant Large Quantitative Model and its version.

03

Review and approve

Give the decision an owner, reviewer and retained record.

WHY FINANCEGPT

Make AI finance work usable beyond the chat.

Inputs and intended use

Identify the data, period, entity, assumptions and intended decision. A review has a defined scope; it does not establish that every source is authentic or every obligation has been captured.

Evaluation and exceptions

Use the LQM and model benchmarking workspaces for model evaluation. Use Connected Evidence for cash relationships and unresolved differences. Keep quantitative results and human judgments distinguishable.

Review and accountability

Use existing governance and workspace approval controls to record review and authorized action. A successful calculation is not an approval, and an approval is not a guarantee of regulatory compliance.

PAID WORKSPACES

Keep the evidence, review and accountability with the work.

Start with one finance workflow. Move to a paid workspace when your team needs retained records, controlled access and repeatable reviews.

AI for finance, across your workflow.

Explore finance AI, AI in finance and AI for finance. For calculations, financial models and deliverables, use the finance AI tools in FinanceGPT Tools, including Build.

Put accountable AI finance work into production.

Start with a finance workflow, then bring the evidence, evaluation and human review together.