In layman’s terms, trade surveillance refers to overseeing trades and transactions to identify discrepancies and irregular patterns. In the financial world, trade surveillance is an investigation of an entity or organisation that can lead to illegal practices and legal litigation.
With the advent of various technologies and traders’ transcending geographical boundaries, trading has become a complicated and widespread practice. Automation has made it possible to carry out trading in seconds or even microseconds.
Traders’ manipulating the market has diminished investors’ confidence. Such circumstances prompt the regulators to deploy stringent measures to remove financial institutions’ above-mentioned hurdles and safeguard investors’ interests.
Challenges in Trade Surveillance
In today’s times, a ‘one shoe fits all’ approach to trade surveillance is not compelling, as it has become much more complicated. Financial institutions must adopt sophisticated models to identify and monitor suspicious patterns of market abuse.
Few main challenges entities have had to face are:
- Overseeing pre-trade communications
- Governance of trades across worldwide markets
- Deployment of measures to comply with complex global regulations
- Assessment of reason(s) and incentive(s) for indulging in market manipulation
- Analysis of shift in buy-side stakeholders from laggard to early adopters
- Inaccuracies in static or generic models, resulting in false positives
- Control of unregulated markets
- Oversight of or inadequate expertise to evaluate psychological state of traders
Trade Surveillance – Next Steps
The following steps in trade surveillance are aimed at countering four crucial aspects in identifying irregular patterns:
- Ensuring Accuracy: The analytics model should be advanced to provide unprecedented accuracy, including governance of communications and trade activities. It should also be effective for a swathe of asset classes, data types, trade types, etc.
- Extensive Workflows: Comprehensive and effective workflows drawing more data and information from divergent trading sources and asset classes can help mitigate the workload in managing investigating alerts.
- Evaluation Of Behavioural Patterns: All stakeholders trade to profit. While such constructive practices are not necessarily wrong, greed and fear drive market manipulation. Such intent from a ‘few bad apples' leads to pricing mechanism distortion and, thereby, artificial pricing and unequal circumstances. It is not enough to address the anomaly after an event has occurred. This is where user behaviour assessment becomes significant. This practice can help firms identify the underlying threats other models cannot.
- Data Utilisation And Management: Adopting integration, cleansing, validation and standardisation measures can ensure data accuracy. The idea is to make sure data can be audited across multiple platforms and sources for easing compliance and other operational tasks for financial institutions.
Conclusion
This article covered trade surveillance challenges, including the following steps becoming more critical than ever before. With extensive compliance and advanced regulations, financial institutions must conduct proper due diligence and deploy measures to steer trade surveillance holistically and efficiently with minimal operational and cost burden.
