Insider Trading Detection: Analytics for Banking Securities

Use transaction analytics and communication patterns to detect potential insider trading in bank securities and investment products.

## Background

SEBI detected 847 insider trading cases in 2024, with several involving bank employees trading on non-public information. A leading private bank wants to proactively monitor employee trading patterns.

## Scenario

You are building a surveillance system for a bank's compliance team. The system must:
- Monitor employee trading in bank securities
- Detect unusual patterns before earnings announcements
- Cross-reference with access to sensitive information
- Flag potential violations for investigation

## Available Data

- Employee trading records (last 3 years)
- System access logs (which databases/files accessed)
- Organizational hierarchy and role changes
- Earnings announcement dates and blackout periods
- Communication metadata (email patterns, not content)
- Market data (stock prices, volumes)

## Detection Challenges

- Distinguish legitimate trading from insider trading
- Account for family member trading
- Handle delayed reporting requirements
- Consider pre-clearance approvals

## Regulatory Framework

- SEBI PIT Regulations 2015
- Bank's Internal Code of Conduct
- Trading window restrictions
- Disclosure requirements

Internal Data:
- Employee Trading Database
- Access Control Logs
- HR Records (roles, departments)
- Pre-clearance Request System
- Compliance Training Records

Market Data:
- Bank Stock Price History (NSE/BSE)
- Trading Volume Data
- Analyst Recommendations
- Earnings Announcement Dates

Data Fields:
- Employee ID, Department, Role Level
- Trade Date, Security, Quantity, Value
- Pre-clearance Reference Number
- System Access Timestamps
- Database/File Access Events
- Earnings Announcement Dates
- Blackout Period Flags

Data Quality:
- Self-reported trades (may have delays)
- Family trading requires separate tracking
- Access logs may have gaps
- Role changes not always updated promptly

Detection Framework:

1. Temporal Analysis
- Trading before announcements
- Pattern changes over time
- Blackout period violations

2. Network Analysis
- Information flow patterns
- Employee communication networks
- Department-level clustering

3. Statistical Tests
- Abnormal return analysis
- Comparison with baseline trading
- Benford's Law for trade sizes

4. Risk Scoring Model
- Access level × Trading activity
- Timing relative to announcements
- Historical compliance record

Implementation:
- Daily batch processing
- Alert threshold calibration
- Case management workflow
- Audit trail maintenance

Tools:
- Python/R for statistical analysis
- SQL for data extraction
- Tableau/PowerBI for dashboards
- Workflow management system