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Key Ingredients for Implementing Successful Holistic Trade Surveillance

In an earlier article, I had explained why there is a need for financial institutions (FIs) to implement holistic trade surveillance.

For e.g., in holistic trade surveillance, an alert that suggests a potential insider trading incident would be analyzed alongside the communication between the trader and the

Without such integrated trade and communication surveillance and analysis, it would be challenging for the surveillance team to decisively prove that the trade was executed based upon insider information.

Following are some of the key characteristic of holistic trade surveillance: It brings together trade, market, voice and written communication, and other relevant data points, to enable an integrated picture.

It aggregates data from myriad disparate sources - including emails, voice, video, text messaging, IM chats, memos, user &

It involves holistic data collection and analysis of a) trade related data including those of client, trader, broker, etc., b) trade related communication between individuals/entities, c) info distributed in the market during the given period, d)

Is imperative for effectively meeting the regulatory requirements such as those of MiFID II which demands that all pre-, at-, and post-trade data (including associated voice and text communications) be automatically brought together for trade reconstruction

Similarly, holistic trade surveillance is crucial to fulfil the Dodd-Frank Act requirement of complete audit trail for enabling accurate and comprehensive trade reconstructions.

Defining robust strategy vis-à-vis governance and control, communication surveillance and monitoring, solution build-versus-buy decision (on-premise, cloud, hybrid), and leveraging of “golden data source” for value maximization is crucial.

FIs’ trade surveillance system should be well integrated with the GRC and operational risk management systems so as to provide more quantifiable conduct related data about the traders and trades.

Robust and consistent global coverage across concerned markets, regulatory jurisdictions, lines of business, communications, trading venues and asset classes and instruments

A web-based, centralized and fully integrated case management solution is needed to support streamlined and integrated workflow and reporting, investigative workbench, efficient

Solution should enable advanced market visualization capabilities – for e.g., by displaying the alerts along with market activity and transactions – so

as to allow compliance analysts to visualize watch list networks, market data and news, trades, orders, positions, control rooms and chat rooms communication etc.

To enable truly holistic trade surveillance, seamless sourcing and contextualizing of both structured and unstructured data – including new and historic transactions, orders, trades, positions, market data, trade and communication alerts,

To overcome this challenge, FIs should focus on optimally automating the data capture, indexing and harmonizing process and leverage big data and data lake capabilities.

By utilizing data lake, data loss would be minimized, data integrity ensured, data silos removed, and more varieties of data stored.

To help support electronic communication analysis, FIs should leverage, as appropriate, robust semantic (NoSQL / NoREL) database management systems, data stores and highly scalable in-memory data grid such as Cassandra, Apache Hadoop &

Neurensic’s SCORE platform combines high-speed, big data processing capabilities with self-adaptive pattern recognition technology – to provide firms with continuous assessment of compliance risk associated with complex trading behaviors.

4) Advanced analytics: FIs should leverage predictive analytics, sentiment analytics and other advanced analytics (such as those referred below) for anomalous trading behavior detection, enabling risk-based discovery, supporting cross-asset-class

In combination with self-service and intuitive web interface, analysts can collaborate on the “original data” – which has not been aggregated/summarized or moved to separate visualization server.

Also, behavioral analytics data gets automatically correlated with traditional alerts within the case management tool, thereby providing surveillance analyst with additional context for the alert.

While embedding ML capabilities in their holistic trade surveillance solution, FIs should first investigate the quality of historical data used for training the system and ensure it is optimal.

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