Banking Agent OS

AI-powered banking system for intelligent agents - 智能体银行交易系统

Overview

Banking Agent OS is a comprehensive banking platform designed specifically for AI agents and intelligent systems. It provides secure account management, transaction processing, AI-powered customer service, and advanced risk control.

Perfect for building:

• AI Agent Banking Systems
• Marketplace Transaction Platforms
• Digital Wallet Services
• Automated Risk Management Systems

Key Features

1. Account Management

• Multi-type accounts: Checking, Savings, Agent Wallet, Escrow
• Real-time balance tracking: Instant updates and queries
• Account freeze/unfreeze: Security controls
• Multi-currency support: USD and more
• User and agent accounts: Flexible account types

2. Transaction System

• Secure fund transfers: Atomic transactions with rollback
• Deposits and withdrawals: Full support
• Payment processing: Real-time execution
• Transaction history: Complete audit trail
• Automated reconciliation: Balance verification

3. AI-Powered Services (OpenAI GPT-4)

• Intelligent customer support: AI chatbot for banking queries
• Transaction analysis: Insights and patterns
• Personalized financial advice: AI-generated recommendations
• Anomaly detection: Unusual pattern recognition
• Fraud prevention: AI-powered security

4. Risk Control

• Real-time risk assessment: 0.0-1.0 scoring
• Transaction limit enforcement: Daily limits and velocity checks
• Velocity checking: Rapid transaction detection
• Fraud detection algorithms: Multiple risk indicators
• Comprehensive risk reporting: Detailed analytics

Technology Stack

Backend:

• Python 3.9+
• FastAPI framework
• SQLAlchemy 2.0 (async)
• Pydantic 2.0 for validation
• OpenAI GPT-4

Frontend SDK (optional):

• TypeScript
• Node.js 16+
• Axios HTTP client

Installation

Prerequisites

Required:

• Python 3.9 or higher
• OpenAI API Key (get from https://platform.openai.com/api-keys)

Optional (for JavaScript SDK):

• Node.js 16+ and npm

Method 1: Python Package via PyPI (Recommended)

# Install the package
pip install banking-agent-os

# Create configuration file
cat > .env \x3C\x3C EOF
OPENAI_API_KEY=your_openai_api_key_here
DATABASE_URL=sqlite+aiosqlite:///./banking_agent.db
EOF

# Start the server
python -m uvicorn app.main:app --host 0.0.0.0 --port 8000

Method 2: JavaScript SDK via npm (For SDK Users)

# Install the SDK
npm install openclaw-banking-agent-os

Then use in your Node.js/TypeScript project:

import { BankingAgentClient, AccountType } from 'openclaw-banking-agent-os';

const client = new BankingAgentClient({
  baseURL: 'http://localhost:8000'  // Points to running backend
});

Note: The npm package is a client SDK only. You still need the Python backend running.

Method 3: ClawHub Installation

# Install via ClawHub
clawhub install banking-agent-os

# The skill will be installed in your skills directory
cd skills/banking-agent-os

# Configure environment
cp .env.example .env
# Edit .env to add your OPENAI_API_KEY

# Start server
python -m uvicorn app.main:app --host 0.0.0.0 --port 8000

Quick Start

1. Ensure Python Backend is Running

Before using the banking system, the backend server must be running:

# Check if server is running
curl http://localhost:8000/health

# If not running, start it:
python -m uvicorn app.main:app --host 0.0.0.0 --port 8000

Expected response:

{
  "status": "healthy",
  "database": "connected",
  "ai_service": "ready"
}

2. Create an Account

curl -X POST http://localhost:8000/api/accounts \
  -H 'Content-Type: application/json' \
  -d '{
    "user_id": "user_123",
    "account_type": "checking",
    "currency": "USD",
    "initial_balance": 1000.00
  }'

Response:

{
  "id": "acc_xxx",
  "account_number": "ACC123456",
  "balance": 1000.00,
  "status": "active"
}

3. Transfer Funds

curl -X POST http://localhost:8000/api/transactions \
  -H 'Content-Type: application/json' \
  -d '{
    "from_account_id": "acc_xxx",
    "to_account_id": "acc_yyy",
    "amount": 100.00,
    "transaction_type": "transfer",
    "description": "Payment"
  }'

4. AI Customer Support

curl -X POST http://localhost:8000/api/ai/chat \
  -H 'Content-Type: application/json' \
  -d '{
    "message": "How do I check my account balance?"
  }'

API Endpoints

Accounts (3 endpoints)

• POST /api/accounts - Create new account
• GET /api/accounts/{account_id} - Get account details
• GET /api/accounts/user/{user_id} - Get user's accounts

Transactions (3 endpoints)

• POST /api/transactions - Create transaction
• GET /api/transactions/{transaction_id} - Get transaction details
• GET /api/transactions/account/{account_id} - Get account transactions

AI Service (4 endpoints)

• POST /api/ai/chat - AI customer support
• POST /api/ai/analyze-transaction - Analyze transaction
• POST /api/ai/financial-advice - Get financial advice
• POST /api/ai/detect-anomalies - Detect anomalies

Risk Control (2 endpoints)

• POST /api/risk/assess - Assess transaction risk
• GET /api/risk/report/{account_id} - Get risk report

System (2 endpoints)

• GET / - Root endpoint
• GET /health - Health check

Usage Examples

Python API Usage

import uvicorn
from app.main import app

# Start the server programmatically
if __name__ == "__main__":
    uvicorn.run(
        app,
        host="0.0.0.0",
        port=8000,
        log_level="info"
    )

TypeScript SDK Usage

import { BankingAgentClient, AccountType, TransactionType } from 'openclaw-banking-agent-os';

// Initialize client
const client = new BankingAgentClient({
  baseURL: 'http://localhost:8000'
});

// Create account
const account = await client.accounts.create({
  user_id: 'user_123',
  account_type: AccountType.CHECKING,
  initial_balance: 1000.00
});

console.log('Account created:', account.account_number);

// Process transaction
const transaction = await client.transactions.create({
  from_account_id: account.id,
  to_account_id: recipient_id,
  amount: 100.00,
  currency: 'USD',
  transaction_type: TransactionType.TRANSFER,
  description: 'Payment'
});

console.log('Transaction completed:', transaction.id);

// AI chat
const response = await client.ai.chat({
  message: 'How do I transfer money?'
});

console.log('AI Response:', response.response);

JavaScript (CommonJS) Usage

const { BankingAgentClient } = require('openclaw-banking-agent-os');

const client = new BankingAgentClient({
  baseURL: 'http://localhost:8000'
});

async function main() {
  // Create account
  const account = await client.accounts.create({
    user_id: 'user_123',
    account_type: 'checking',
    initial_balance: 1000.00
  });

  console.log('Account created:', account.id);
}

main();

Use Cases

1. AI Agent Banking

Autonomous agents that need their own financial accounts and transaction capabilities.

2. Marketplace Transactions

E-commerce platforms with escrow services and automated payouts.

3. Digital Wallet Services

Agent wallet management with real-time balance tracking.

4. Risk Management

Real-time fraud detection and prevention for all transactions.

Configuration

Required Environment Variables

# REQUIRED: OpenAI API Key for AI features
OPENAI_API_KEY=sk-...

# OPTIONAL: Database configuration (defaults to SQLite)
DATABASE_URL=sqlite+aiosqlite:///./banking_agent.db

# For production, use PostgreSQL:
# DATABASE_URL=postgresql+asyncpg://user:password@localhost/banking_agent

Python Dependencies

When installed via pip install banking-agent-os, all dependencies are automatically installed:

• fastapi>=0.104.0
• uvicorn[standard]>=0.24.0
• sqlalchemy>=2.0.0
• aiosqlite>=0.19.0
• pydantic>=2.0.0
• openai>=1.0.0
• python-dotenv>=1.0.0

Node.js Dependencies (SDK Only)

When installed via npm install openclaw-banking-agent-os:

• axios
• TypeScript types included

Security Considerations

API Key Safety

• Never commit .env files to version control
• Store OPENAI_API_KEY securely
• Rotate API keys regularly
• Use environment-specific keys

Input Validation

• All inputs validated with Pydantic
• SQL injection protection via SQLAlchemy
• Type checking throughout

Transaction Safety

• Atomic operations with rollback
• Balance verification
• Risk assessment for all transactions
• Fraud detection enabled

Platform Links

Documentation

• Quick Start: QUICKSTART.md
• API Documentation: API_DOCUMENTATION.md
• Architecture: ARCHITECTURE.md
• Full README: README.md

Testing

The package includes comprehensive tests. After installation:

# Install test dependencies
pip install pytest pytest-asyncio httpx

# Run tests
pytest tests/ -v

Troubleshooting

Q: AI features not working?

A: Ensure OPENAI_API_KEY is set in your .env file. Get a key from https://platform.openai.com/api-keys

Q: Database errors?

A: Check DATABASE_URL configuration. SQLite is fine for development. Use PostgreSQL for production.

Q: Import errors?

A: Ensure package is installed: pip install banking-agent-os

Q: Port already in use?

A: Change port: uvicorn app.main:app --port 8001

Q: TypeScript SDK can't connect?

A: Ensure Python backend is running at the correct URL. Check baseURL in client configuration.

Performance

• Transaction Processing: \x3C 100ms average
• AI Response Time: 1-3 seconds (depends on OpenAI)
• Concurrent Users: Supports 100+ concurrent connections
• Database: Async SQLAlchemy for high performance

Roadmap

v1.1.0 (Planned)

• Rate limiting and throttling
• Webhook notifications
• Enhanced fraud detection models
• Multi-language support for AI

v1.2.0 (Planned)

• Real-time WebSocket updates
• Advanced analytics dashboard
• Batch transaction processing
• Enhanced security features

Support

• GitHub Issues: https://github.com/ZhenStaff/openclaw-banking-agent-os/issues
• Email: [email protected]
• Documentation: https://github.com/ZhenStaff/openclaw-banking-agent-os#readme

License

MIT License - see LICENSE file for details.

Authors

• OpenClaw Team - Initial work and maintenance
• Contributors - See GitHub contributors

Version: 1.0.0 Last Updated: 2026-03-09 Status: Production Ready Installation: pip install banking-agent-os or clawhub install banking-agent-os