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Fintech Partnership Targets "False Positive" Crisis in Market Surveillance
Abstract:A new partnership between BMLL and Features Analytics aims to overhaul market abuse detection by integrating deep historical order book data to reduce surveillance false positives.

BMLL, an independent provider of historical Level 3 data, has formed a strategic alliance with AI surveillance firm Features Analytics to tackle inefficiencies in market abuse detection. The collaboration addresses the overwhelming volume of false positive alerts generated by legacy rule-based systems.
The Cost of Compliance Noise
Financial institutions currently face significant operational drag from surveillance systems that flag non-suspicious activity. Features Analytics claims its “eyeDES” technology can reduce these false positives by 90%, a figure that becomes actionable when paired with BMLLs granular order book reconstruction capabilities.
- Reduction in False Positives: Targeting a 90% decrease via AI-driven screening.
- Surveillance Benchmarking: Validating monitoring systems against historical market conditions for regulatory explainability.
Cross-Asset Implications
While the initial focus includes global equities and ETFs, the technology has implications for the broader financial ecosystem, including Foreign Exchange (FX). The move mirrors recent trends; the London Stock Exchange Group (LSEG) recently launched a similar cross-venue platform targeting FX and MiFID instruments.
Disclaimer:
The views in this article only represent the author's personal views, and do not constitute investment advice on this platform. This platform does not guarantee the accuracy, completeness and timeliness of the information in the article, and will not be liable for any loss caused by the use of or reliance on the information in the article.

