AI & Machine Learning
Post Trade Compliance
Guide post-trade compliance monitoring and trade surveillance system design. Use when building alert logic to detect churning, front-running, cherry-picking, layering, spoofing, wash trading, or marking the close, implementing post-trade best execution review, evaluating allocation fairness with pro-rata verification or dispersion analysis, designing exception-based monitoring workflows with escalation paths, correlating trading with MNPI events for insider trading detection, building personal trading surveillance for preclearance and blackout enforcement, determining SAR or blue sheet or CAT reporting triggers, or tuning surveillance thresholds to reduce false positives. Also covers turnover ratios, cost-to-equity ratios, and investigation case management.
- Publisher / source
- JoelLewis/finance_skills (found on skills.sh)
- Upstream record
- JoelLewis/finance_skills
- Version
- Version 3
- Published
- Publication review
- Approved for publication
- Content fingerprint
024efac70e907331d013b534f7ed667078c3cd9e2361023fa944573056055c77