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RECOGNITION · PROGRAMMES · ECOSYSTEM · TRUST FinanceGPT Developers
QUANT & RISK APIs

Add institutional quantitative and risk capabilities.

Use FinanceGPT quantitative capabilities for portfolio analysis, scenarios, risk, optimization and structured investment research while keeping model lineage and authority boundaries explicit.

Answer-first: FinanceGPT Quant & Risk APIs expose governed quantitative financial capabilities for applications that need structured numerical analysis rather than free-form language as the numeric authority.

FinanceGPT Developers
intent = "forecast liquidity"evidence = workspace.data()model = LQM.run(evidence)reasoning = QLM.compose(model)action = policy.review(reasoning)
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Data & evidenceQuantitative modelLanguage orchestrationGoverned tools
CAPABILITIES

What this workflow brings together.

The public page explains the outcome first, then keeps the underlying financial methods, evidence and review path visible.

Portfolio analytics
Risk and scenario analysis
Quantitative research
Optimization
Model lineage
Structured numerical outputs
Separate investment and Financial Actions authority
HOW IT WORKS

From intent to reviewable output.

FinanceGPT should make complex financial work easier to express without hiding the evidence, calculations or control points.

Prototype against sandbox data and bounded workspace context.
Select the quantitative operation required by the application.
Validate model inputs and numerical outputs.
Observe latency, errors and request evidence.
Request production access through the Developer commercial funnel.