Spotting Risky Trades – Before They Do Damage


How do you spot market manipulation in real time?

Name of Organization: Euronext

Industry: Financial services

Location: Lisbon, Portugal

Business Opportunity or Challenge Encountered:

Euronext, now the European trading market, needed near-real-time surveillance of financial markets and a faster fraud analytics engine. The exchange, which offers financial products and services in cash equities, futures, options, bonds, market data, and other products, found it was being overwhelmed with data.

With steadily growing data volumes, analysts found it increasingly difficult to process data within their traditional database structure — especially when searching for questionable trading activity. Euronext executives observed that the biggest problem they had was in market surveillance and fraud analytics.  Finding manipulation was complex because analysts needed to manually sift through and correlate large amounts of information.

Managers at the exchange, formerly affiliated with the New York Stock Exchange, sought to uncover questionable trading patterns by using powerful detection algorithms. With rapidly expanding transaction volume, securities markets not only need processing power, but also the flexibility to incorporate new algorithms that can spot risks—such as questionable trading activity—before they can do damage.

Euronext’s analysts found that their ability to uncover patterns buried deep within billions of trades required a simple approach to a complex problem. The exchange needed an anti-manipulation and fraud analytics solution that could analyze huge volumes of data – expected to scale into the multi-petabyte range – in near real time.

How This Business Opportunity or Challenge Was Met:

Euronext turned to a high-volume analytics engine to speed and simplify analytic processes, so that even as the volume of securities trading continues to grow, the exchange has the capability to help maintain a level playing field for all investors.

The system, IBM PureData System for Analytics, is a data warehouse appliance capable of being plugged into high-volume transaction environments. This helped speed and simplify analytic processes for capacity planning, operational assessment, and compliance and regulation.

Euronext also moved its derivatives market data channels to an upgraded XDP infrastructure, intended to enhance the overall performance of the market data real-time feed and in particular the latency. The Euronext Derivatives XDP feed provides high-speed, real-time market data for Euronext Derivatives markets.

Measurable/Quantifiable and “Soft” Benefits From This Initiative:

Moving its analytic data warehouse appliance helped Euronext reduce the time and cost IT staff spent delivering analytic services to the business, including a 35 percent decrease in the number of IT resources required to support the solution.

With the implementation, Euronext reduced the time to run market surveillance algorithms by more than 99 percent. This enabled surveillance experts to design and test many more algorithms to spot emerging trends in insider trading and market manipulation. Previously, these activities would often run more than 24 hours.

The new platform is also expected to help the organization create a self-service environment that speeds time-to-market and lowers costs for new business intelligence activities.

(Sources: Euronext, IBM)

(Editor’s note: Euronext was NYSE Euronext, affiliated with the New York Stock Exchange, at the time these events took place.)

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