Financial Risk Scanner for Listed Companies

Financial Risk Scanner

Scan listed company financial statements for potential fraud signals and accounting anomalies using Tushare data APIs.

Quick Start

python3 scripts/analyze_company.py 

Example:

python3 scripts/analyze_company.py 000001.SZ

Workflow

1. Fetch Financial Data: Retrieve 10+ years of annual financial statements (balance sheet, income statement, cash flow statement) via Tushare 2. Calculate Risk Metrics: Compute 21 risk indicators with historical trend analysis 3. Cross-validate: Check company announcements for supporting evidence when anomalies detected 4. Generate Report: Produce structured risk assessment with severity ratings and recommendations

Risk Indicators

| Category | Indicator | Detection Criteria | |----------|-----------|-------------------| | Asset Reality | Cash-Debt Paradox | Cash > 15% assets + Interest-bearing debt > 30% assets | | | Receivables Anomaly | Receivables growth >> Revenue growth | | | Inventory Anomaly | Inventory growth >> COGS growth | | | Prepayments Surge | Prepayments > 5% assets without business rationale | | | Other Receivables High | Other receivables > 5% net assets | | | Construction Suspended | Construction long uncompleted or excessive | | Profit Quality | Cash-Profit Divergence | High profit + Negative operating cash flow (3+ years) | | | Gross Margin Anomaly | GM far above peers or rising persistently | | | Sales Expense Anomaly | Sales expense ratio far below peers | | | Abnormal Non-recurring | Non-recurring items > 30% of profit | | | Asset Impairment Bath | One-time large impairment charges | | Related Party | Related Transaction High | Related purchase/sales > 30% | | | Related Fund Flows | Related party in other receivables/payables high | | | Related Guarantees | External guarantees > 50% net assets | | Capital Structure | Goodwill High | Goodwill > 30% net assets | | | Debt Ratio High | Debt ratio > 70% and rising | | | Short-term Liquidity | Short-term debt / Cash > 3x | | | Dual Debt High | Long + Short debt high with cash strain | | Audit & Governance | Auditor Changes | Consecutive auditor changes | | | Non-standard Opinion | Audit opinion with emphasis or reservation | | | Executive Departures | CFO/Board secretary frequent changes |

Key Metrics Formulas

Cash-Debt Paradox Ratio = (Cash / Total Assets) × (Interest Debt / Total Assets)
Cash-Profit Ratio = Operating Cash Flow / Net Profit (threshold: < 0.5 for 3+ years)
Receivables Growth Ratio = Receivables Growth Rate / Revenue Growth Rate
Inventory Turnover Ratio = COGS / Average Inventory
Gross Margin = (Revenue - COGS) / Revenue
Debt Ratio = Total Liabilities / Total Assets
Liquidity Pressure = Short-term Borrowing / Cash Balance

References

For detailed detection logic and thresholds, see references/risk_indicators.md.

Cross-Validation Sources

When anomalies are detected, cross-validate with:

Output Format

Reports are saved to ~/.openclaw/workspace/memory/financial-risk/_.md

Report sections: 1. Company Overview: Basic info, industry, listing date 2. Risk Summary: Total risks, severity distribution, top concerns 3. Detailed Analysis: Each indicator with historical trend charts 4. Cross-validation: Supporting evidence from announcements 5. Recommendations: Priority actions and monitoring points

Severity Levels

| Level | Symbol | Criteria | |-------|--------|----------| | Critical | 🔴 | Multiple indicators triggered, strong fraud signals | | High | 🟠 | Single strong indicator or 3+ moderate signals | | Moderate | 🟡 | Anomaly detected but needs verification | | Low | 🟢 | Minor concern, monitor periodically |

Environment Variables

| Variable | Required | Description | |----------|:--------:|-------------| | TUSHARE_TOKEN | ✅ Yes | Tushare Pro API Token for Chinese A-share market data |

How to obtain TUSHARE_TOKEN: 1. Register at https://tushare.pro/register 2. Get your token from the user center 3. Set environment variable:

   export TUSHARE_TOKEN="your_token_here"
   

Python Dependencies

| Package | Version | Purpose | |---------|---------|---------| | tushare | >=1.2.0 | A-share market data API | | pandas | >=1.3.0 | Data manipulation and analysis |

Install dependencies:

pip install tushare pandas

Notes

Limitations

| Limitation | Description | |------------|-------------| | API Token Required | Requires a Tushare Pro API token to fetch data | | Market Scope | Only supports Chinese A-share market listed companies | | Historical Data | Limited to last 10 years of financial data | | Related Party Data | Transaction data with related parties requires manual verification from annual report notes | | Industry Comparison | Some industry metrics may not have sufficient peer data for comparison |

Data Sources

| Source | Type | Description | |--------|------|-------------| | Tushare Pro API | Primary | Chinese A-share financial data, market data, and announcements |

Provenance

| Field | Value | |-------|-------| | Author | laigen | | License | MIT | | Homepage | https://clawhub.ai/skills/financial-risk-scanner | | Registry | ClawHub |

python3 scripts/analyze_company.py 

Example:

python3 scripts/analyze_company.py 000001.SZ