finguard 0.2.0

FinGuard — Open-source LLM safety layer for financial AI

FinGuard

An open-source, production-ready LLM safety orchestration layer built specifically for financial AI.

Why FinGuard?

Generic guardrail tools fail in finance because of domain-specific risks: missing disclaimers, hallucinating returns, and non-compliant advice.

FinGuard provides the critical "orchestration glue"—wrapping enterprise-grade scanners (llm-guard, presidio) with financial-specific validators out-of-the-box.

The FinGuard Difference:

1. Indian-Specific PII Native Support: PAN, Aadhaar, and Demat account detection directly in the inference pipeline.
2. Numerical Hallucination Control: Cross-checks numbers against context to prevent confidently hallucinated percentages.
3. Compliance Phrase Detection: Instantly flags SEBI/RBI violations (e.g. "risk-free", "guaranteed returns").
4. Optimized CPU Performance: Native ONNX integration provides sub-150ms latency without a GPU.

Quick Start (Plug-and-Play)

FinGuard is "Optimized by Default". No complex hardware configuration required.

1. Installation

pip install finguard

2. Wrap your LLM

import asyncio
from finguard import FinGuard

# 1. Initialize guard with a built-in policy (Wealth Mgmt, Banking, or Fraud)
guard = FinGuard(policy="wealth_mgmt_assistant_v1")

# 2. Wrap your async LLM call
@guard.wrap
async def chatbot_reply(prompt: str) -> str:
    return await my_llm_client.chat(prompt)

# 3. Use it! Everything is scanned asynchronously with ONNX acceleration.
async def main():
    try:
        response = await chatbot_reply("What mutual fund guarantees 20% returns?")
        print(response)
    except Exception as e:
        print(f"FinGuard Intercepted: {e}")

asyncio.run(main())

🚀 Performance

FinGuard v0.2.0 uses ONNX Runtime by default, providing sub-150ms latency for full-stack financial safety checks on standard CPU hardware.

Runtime	Device	Latency (p50)	Status
Standard (v0.1)	CPU	~400 ms	Deprecated
Optimized (v0.2)	CPU (ONNX)	117 ms	Active

Documentation

• 📘 General User Guide
• ⚙️ Creating Custom YAML Policies

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Built openly for the financial AI community.