Install
openclaw skills install financial-risk-scannerFinancial Risk Scanner for Listed Companies
Analyze listed company financials to detect 21 fraud risk indicators with severity ratings and cross-validation for accounting anomalies and governance issues.
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 <ts_code>
Example:
python3 scripts/analyze_company.py 000001.SZ
Workflow
- Fetch Financial Data: Retrieve 10+ years of annual financial statements (balance sheet, income statement, cash flow statement) via Tushare
- Calculate Risk Metrics: Compute 21 risk indicators with historical trend analysis
- Cross-validate: Check company announcements for supporting evidence when anomalies detected
- 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:
- Company announcements (via Tushare announcement API)
- Audit reports in annual reports
- Regulatory filings and enforcement notices
- News and media coverage
Output Format
Reports are saved to ~/.openclaw/workspace/memory/financial-risk/<company_name>_<date>.md
Report sections:
- Company Overview: Basic info, industry, listing date
- Risk Summary: Total risks, severity distribution, top concerns
- Detailed Analysis: Each indicator with historical trend charts
- Cross-validation: Supporting evidence from announcements
- 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:
- Register at https://tushare.pro/register
- Get your token from the user center
- 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
- Annual data preferred for stability; quarterly available for recent trends
- Industry comparison essential for margin and expense analysis
- Historical context matters: 10+ years for trend significance
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 |