Financial 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

bash

python3 scripts/analyze_company.py <ts_code>

Example:

bash

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

text

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:

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:

   bash

   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:

bash

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