The StreamBase Event Processing Blog

Chasing an Ambulance Full of BATS

The high-profile trading failure at BATS this week sparked a rash of negative publicity, gracing the front page of media outlets from the Wall Street Journal to Forbes. In the software industry, more software companies have proclaimed their techology would have sheltered BATS from their storm than cheap umbrella sidewalk vendors on a rainy day in New York City.

An especially troubling rash of "thought leadership" came from my own industry - real-time analytics and complex event processing. Forbes, for example, published an article by SAP (who sells a CEP product) BATS hits the rocks, which may have lifted its sales that proclaims that the BATS incident portends that "CEP technology is about to move from the backwaters of data management technology to center stage."

In Wall Street and Technology, John Bates, the CTO of Progress Software was quoted in the artice Flash Crash at BATS renews Market Concerns to say firms "clearly lacked adequate risk controls such as real-time surveillance and monitoring. Hopefully this incident serves as a wake up call." What kind of software do you think Bates sells?  Drum roll please... real-time surveillence and monitoring!"

My company sells these kinds of solutions too. And I know BATS well (disclosure: BATS is not a StreamBase client), and they are as technologically advanced as any firm in the world. So this kind of ambulance chasing is not only unbecoming, it's also dead wrong. It's like suggesting Formula One racing will be safer if the cars can be made to go faster (CEP) and we do a better job of filming them as they go careening into a wall (monitoring). Indeed, BATS quickly reported that they had a bug in their system, so comments about risk management and surveillance are irrelevent.

That said, there's an issue here for the capital markets - but the issue is cultural, not technological. 

What's happening in the capital markets is that we are in the midst of real-time automation renaissance. 10 years ago, less than 5% of stock trading in the U.S. markets was done algorithmically; today, as much as 70% is done on computer-implemented, and human designed, algorithms.

Larry Tabb, the founder and chief executive of the Tabb Group, said in the Times that “The markets basically gutted their high-cost, nonstop infrastructures for very fast, low-cost infrastructures." Now we are talking - Larry is on the right path!

In software, mistakes happen frequently. Professor Neil Johnson at the University of Miami analyzed 18,520 "ultrafast Black Swan [trading] events" from 2005-2011. In Stock Market Flaws Not So Rare, the New York Times that just one of the 13 U.S. stock exchanges - NASDAQ - declared 139 breakdowns at other exchanges last year alone, up from 69 the year before.

Software breaks. We have a word for it: bugs. But that's not new. What is new is that the errors can do damage so much more quickly, and, because the world is now so hyperconnected, everyone knows about it more quickly than ever before. 

So what is the magic elixir to making the capital markets fast, fair, and safe?  

There are still voices out there that seem to think that the answer is to discontinue the use of computers for automation. Ha! The whining about the evils of capitalism and sophisticated technologies continues to rain down from dissenters posting their admonations from inside their pup tents via shiny new iPad 3's. These dissenters need to Get Over It - technology is here to stay, and its use is expanding quickly from Wall Street to Main Street.

Making automation safe and reliable requires complex, cultural change:

1. Continue to refine reporting requirements. You can't manage what you can't measure. In the United States, exchanges didn't report outages on other exchanges until 2007. Nasdaq reports that there have been 110 outages in the last year like the one that triggered the BATS mishap. Continued measurement and transparency will lead the industry toward greater reliability. With more analysis and reporting, more accountability is possible, and regulators could focus on correlating events among exchanges and brokerages to look for systemic flaws.

2. Refine and lighten regulation; don't just pile it on. Dodd Frank and MIFID 2 have put regulation on the must-do agenda of all firms. But it's still largely up to the reader to separate what's essential from what's fluff, and that's not effective. Exchanges like BATS are extrodinarily regulated - so more, heavier regulation is not the answer.

3. More systemic attention to software quality.  Moore's Law - the idea that the power of computing doubles approximately every two years, does not apply to software quality. The BATS crash shines a light on the issue that is inbred in innovation; the rising importance of software testing, quality, and simulation. Most firms have ad-hoc processes for quality and should have continuous testing, regression testing, and real world simulation. CEP can make systems go faster, and surveillence helps spot problems more quicky, but when more attention is paid to testing and simulation, less errors occur. 

These changes are complex and cultural, not technological. Tools will help, but not solve, the challenge of ensuring a safe, reliable, and fair market.

 

b-next Selects StreamBase: Regulation Goes Real-Time

Today's announcement by StreamBase partner b-next is part of steady shift toward real-time in the capital markets. b-next, a pioneering provider of multi-venue, multi- asset class capital markets surveillance and compliance solutions, announced their selection of StreamBase for their CMC:Suite solution set. By incorporating event processing, b-next's customers, such as regulators, exchanges and banks, will be able to rapidly implement near real-time market abuse surveillance solutions. This will enable relevant market participants to comply with recent ESMA guidelines and future proof themselves against additional regulation expected in the coming years.

Although event processing has often been associated with sub millisecond decision making and algorithmic trading, trading was indeed, just the tip of the iceberg. Pre-trade risk management followed, and now the entire infrastructure of the capital markets applying automation technologies like event processing. b-next’s systems is further evidence of that shift, as the CMC:Suite solution helps reduce compliance officers' response period by helping them immediately identify suspicious trading patterns and generating alerts. All in real-time.

"We're one flash crash away from being required to understand our risk in real-time," the head of electronic trading at a top-tier firm told me recently. His firm has deployed event processing globally to manage their trade flow, risk, and positions. After years of being deployed in the heart of electronic trading systems, recently the technology has been increasingly used to manage the same automated infrastructure its often used to power. 

We welcome our newest partner b-next to the StreamBase family!

About b-next

b-next is a provider of multi-venue, multi-asset class, Capital Markets Surveillance and Compliance software solutions to manage risk, meet regulatory mandates and drive trading efficiencies. The b-next Capital Markets Compliance (CMC) solution offers  a single integrated compliance platform for Market Abuse, Insider Trading, Conflict of Interest, Derivatives/OTC Monitoring, Best Execution, Fraud Detection and Prevention, AML and more. With over 150 customers, b-next has a 20 year history of delivering solutions to market participants, exchanges and capital markets regulators.

Introducing Live BI and StreamBase LiveView

For some time now, StreamBase has been working on a new product concept that's a little bit CEP, a little bit data warehouse, and a little bit business intelligence. Today we've unveiled it as StreamBase LiveView. Our customers have called it a "game changer," and a product that "fills a massive hole in the BI space." Hyperbole like that needs to be backed up, so here we go.

Complex event processing (introduction on Google+) was envisioned by its inventors as a "database for moving data" as firms increasingly deal with data in motion from mobile devices, social media and digitized data of all types, and in all industries. In its first decade of commercial use, CEP has come to power automated trading on Wall Street. A who's who list of firms have been public about their adoption of CEP, so let's examine the live BI problem in the context of Wall Street.

Industry analysts estimate that over 60% of U.S. equities trading is automated. The problem is, with so much automation, it's impossible to see and act on what's going on, because a typical trading environment can generate 10's of millions of events a day. Existing business intelligence and data warehouse tools aren't used in the front office of Wall Street, because they're designed to summarize what's already happened, not what's happening now. 

StreamBase LiveView brings BI and streaming data together, for the first time. Applications that need Live BI are everywhere on Wall Street - trading risk management, position management, P&L management, surveillance, compliance, and trading itself, as Waters Technology magazine describes in the article that StreamBase Seeks 'Radical Transparancy' in Business Intelligence.

And applications in other markets can be found in any environment that has big data in motion: telecom (location aware insight and live network operations), security (live fraud detection, live surveillance), and e-commerce (live social media analytics, ad placement, big streaming analytics for Hadoop and Flume). These apps can be deployed on premise or distributed in the cloud. 

StreamBase LiveView is built with StreamBase CEP, which provides connectivity to over 125 event-based sources of data and the extreme scalability required by live BI. The server-based architecture is designed to process hundreds of millions of events per node, absorbed from a network of event sources such as an enterprise message bus or scalable event absorption layer like Flume or IBM Streams. At the front end, users can slice and dice streams of data with ad-hoc query tools in the StreamBase LiveView Desktop (shown above). But here's the key: once users ask the questions they want answered, StreamBase LiveView keeps answering their questions - as conditions change in real-time; users see an always-live view of streaming data.

For the user, all this technology means just one thing: they see business intelligence that's constantly fresh and relevant to their business operations. It's not a view of 5 days ago, or even 5 minutes ago. The data is live, the insight is live, and live insight can lead to live action.

Facebook, Twitter, Google+ give us a live view of what's happening in our social networks; StreamBase LiveVew gives firms a live view of their enterprise data.

To learn more, watch the StreamBase LiveView presentation, follow new materials, articles, and resources on Google+ (+StreamBase and CEO +Mark Palmer), read industry analyst Curt Monash, DMBS2.0, or follow StreamBase Systems (@streambase), CEO Mark Palmer (@mrkwpalmer ), and CTO Richard Tibbetts (@tibbets) on Twitter.

 

Real-Time Big Data and the 11 Principles of Modern Surveillance Systems

(This article is also posted in the TABB Group's TABBForum, and generated a broad discussion in the comments there. To participate, visit the original post here.)

In his TabbFORUM article, Dave Tolladay eloquently argues that real-time surveillance is crucial in today's high-frequency trading landscape, and I agree. Ten years ago, real-time computing began to influence trading; today, HFT is pervasive and existing surveillance techniques, designed to run at the speed of click trading, should be considered to be legacy architectures in need of a radically new, modern approach. 

But managing big data in real-time is a new problem of physics, and those physics come center stage when it comes to surveillance. A recent panel on modern surveillance systems, Miranda Mizen from TABB Group, Justin Amos from Redkite Financial Systems and Richard Tibbetts from StreamBase compared modern surveillance systems to “anti-virus software for trading.” 

In the course of their conversation, Justin, Miranda and Richard touched on 11 key points about the “next generation” architectural requirements for surveillance, including: 

1. Real-time analytics. Surveillance systems must analyze market data at the speed of automated trading. That means real-time computing and complex event processing (CEP) as one of the critical technology enablers of modern surveillance systems. 

2. Historical “big data” analytics. Surveillance systems must put activity in context – suspicious activity can be an aberration or a pattern, based on historical actions. The big data movement has spurred a renaissance in the database industry with firms like Netezza (now IBM), Vertica (now HP), MongoDB (open source) as the flag bearers for the NoSQL (Not Only SQL) database revolution that aims to supplant legacy RDBMS systems to deal with the rising deluge of data described in the Economist piece. In surveillance, “big data analytics” allow on-line access to trade-by-trade history for investigation, trending, and discovery to be mashed up with real-time data to provide a real-time and historical context to behavior. 

3. Inclusion of new types of data sources. Justin suggested that the inclusion of real-time news – and even social media data sources – can be a benefit in correlating, for example, suspicious trading on news. 

4. Data fusion. Real-time, historical and new data sources must be fused for a complete picture of intra-day trading behavior, and a 360 degree view of market data, activity and sentiment. 

5. Multi-asset class support. Since HFT is becoming increasingly cross-asset class, so must modern surveillance systems. 

6. Pre-built algorithms. Todayʼs surveillance systems must support standard algorithms like front running, spiking, tailgating, and ramping that can mistakenly or purposefully occur in computer-based HFT systems. 

7. Adaptive algorithms. The ability to adapt algorithms on the fly to reduce false positives is important, due to the increasingly dynamic capability of modern HFT systems to adapt their behavior. 

8. Algorithm extensibility. The ability to quickly add new algorithms to the system as market dynamics evolve is also a key modern requirement for systems – they must keep pace with the rate of change of modern trading algorithms. 

9. Flexible workflow management and case management. Surveillance systems generally donʼt make automated decisions to change trading behavior or stop trading on their own; instead, they tend to guide a series of workflow steps to alert compliance officers, portfolio managers or traders and manage the process of alert analysis, resolution and tracking. 

10. Accessibility for the business analyst. With regulation changing so quickly, more firms want their own control over surveillance behavior, so some provide tools that allow compliance personnel to discover and implement surveillance algorithms on their own. 

11. Cloud-based or on-premise deployment. Surveillance is not typically the core expertise of trading groups, so the ability to deploy systems either in the cloud or on premise allows for more rapid and global rollout of surveillance tools. 

Real-time big data is a change in computing physics on Wall Street. New requirements motivate new solutions, and the new solutions and innovation coming from the surveillance community continues to prove that innovation never sleeps on Wall Street.

 

StreamBase News at SIFMA

The SIFMA show in New York is always a big week for news for firms that do business in the capital markets. This year, we had so much new news  that we issued a series of announcements over the last several weeks. In case you missed any of them, here's a summary of what we're talking about at SIFMA this year.

1. Thomson Reuters Selects StreamBase CEP. This is a huge endorsement from a leader in the capital markets. Thomson Reuters will utilize StreamBase in their open, global, ultra-high speed and resilient network for the financial industry, Elektron, as an integrated element in their Enterprise Platform for Velocity Analytics, as an embedded CEP engine in Thomson Reuters applications, and in their Thomson Reuters Dealing Aggregator FX Trading Solution. We're very honored to be selected by Thomson Reuters!

2. BMF&BOVESPA Selects StreamBase CEP. The largest exchange operator in South America selected StreamBase as their enterprise-wide deployment platform for event-based applications - yet another huge endorsement and evidence of the increased use of CEP for enterprise-wide deployments. 

3. StreamBase in Asia: Complex Event Processing in Trading with SunGard. Our partner SunGard recently held a online panel discussion about algorithmic trading, market data management, risk management, and other other applications in Hong Kong with Benjamin Becar, algorithmic trading product management for SunGard in Hong Kong, and Richard Tibbetts, StreamBase CTO. You can watch the replay of the session here.

4. New product release: StreamBase 7. Fantastic new usability, and performance improvements in four different dimensions.

5. StreamBase University Program. Our new program to provide StreamBase software and certification resources to universities to help students learn about the growing field of CEP in school. The StreamBase University Program is integrated with our StreamBase Developer Certification Program and StreamBase Component Exchange community for sharing StreamBase integrations, code examples, frameworks, and adapters. 

6. Erjang / Erlang integration and the growing StreamBase Component Exchange Community. The latest contribution from Darach Ennis (@darachennis) has been a big hit in the Erlang community and on SlideShare. Watch it here: Complex Erjang / Erlang Processing with @StreamBase. 

7. CEP in Risk Management and Surveillance. CEP isn't just for algo trading anymore! Broad adoption by firms like Thomson Reuters and BMF&BOVESPA, and increasing use in applications such as risk management and surveillance illustrate that CEP is becoming a strategic platform for firms on Wall Street, and for third party developed applications with "CEP Inside."

8. "Faster than a Flash" - MIT Technology Review on CEP for market data risk management. MIT Technology Review published a story on how proprietary trading firm PhaseCapital used CEP to have ZERO bad trades on the day of the flash crash. While other pundits promote fear of a looming "splash crash" - bigger and worse than the "flash crash," we're simply trying to promote firms that are actually doing something about it with innovative technology approaches to make trading safer.

I'll be at the show in New York this week and addressing questions on Twitter about these developments and others at @mrkwpalmer.

Fast is Good, But Fast and Dumb is Dangerous

Last week I was on a panel at the Bloomberg Enterprise Technology Summit (@BBGlink) with Steve Goldman from CME Group (@CMEGroup), the CTO of NYSE Technologies, Bloomberg TV Markets Reporter Dominic Chu (@The_Domino) and we talked about how speed is important, but that the real innovation going on today is about making applications smarter, not just faster. The conversation was constructive and productive and was re-tweeted all over the internet. 

Then, this weekend, Barron's article "Next Danger: 'Splash Crash'" featured an interview with Progress Software's CTO Dr. John Bates. Barron's cites his view that high frequency trading poses an "extreme risk" of creating a "splash crash," his own term, which he describes as a worse than the flash crash: "trading systems could clog up, limited bandwidth could choke orders, exchanges could freeze up -- splashing across all of the affected asset classes. Pandemonium."

Bates "frets that, absent more oversight, terrorists wielding smart machines could attack the markets in an attempt to cripple our economy,"  and has indeed been fretting publicly for a while now in interviews blog posts, such as:

• "The trouble with algorithms: wild children or reckless parents?"
• "Beware the splash crash"
• "Red flags in morning, firms take warning"
• "When does a rogue trader become a scoundrel?"

It's unhelpful to focus on the fear; we should focus on solutions. Every automated application - from kiosk-based airport check-in to security in a retail store - needs surveillance. Trading is no different. This is not new. What's new is that trading occurs at speeds never before seen, and when things go wrong, it's easy to blame the bankers of nefarious activity.

So today's article in MIT Technology Review, "Faster than a Flash," was a refreshing break from provocative predictions of doom and gloom. MIT features Boston-based proprietary trading firm PhaseCapital (disclosure: PhaseCapital is a StreamBase customer). CEO Eric Pritchett described to MIT reporter Erica Naone that his algorithmically-driven trading firm made NO erroneous trades on the day of the flash crash. 

How did Phase Capital use algorithms and provide a safe trading harbor to their investors on the day of the flash crash? They use the same technology to analyze their market data in real-time that they use to trade in real-time: complex event processing, or CEP (intro here).

Corwin Yu, director of electronic trading for PhaseCapital, explained their innovation this way:

Typically, PhaseCapital processes 30,000 to 40,000 'ticks,' or pieces of market data, per second. During the flash crash, that number jumped to more than 289,000 ticks per second— much of it representing stocks swinging wildly. "A lot of scrubs kicked in and realized that this data didn't make sense," Yu says. For example, some large publicly held companies, such as Accenture, traded for less than $1 during the flash crash. PhaseCapital continued trading, but filtered data that appeared suspicious. Because it didn't act on that data, it was spared erroneous trades.

Yu concluded that speed is essential in the world of trading today, but that the trick is to be "fast and smart." Read about PhaseCapital's innovation in MIT Technology Review.

The solution for a safer market isn't heavy-handed regulation of "wild, reckless algorithms" in order to catch the "scoundrels" of Wall Street. Fast does good on Wall Street; but fast and dumb is dangerous. So we should tune out the fear mongers and tune in to the innovators that can help make Wall Street be fast - and smart.

Thomson Reuters Selects StreamBase CEP for Elektron High-Speed Cloud, Quant Platform, Apps, and FX

Today we're excited to report that Thomson Reuters has selected StreamBase as its complex event processing (CEP) platform for a broad set of initiatives. CEP "flips the database on its head" by providing the ability to monitor, analyze, and act on events happening in real-time, rather than looking in the rear-view-mirror of what happened yesterday, last week, or last month. CEP powers real-time, big data applications on Wall Street including high frequency trading, pre-trade risk management, surveillance, market data management, smart order routing, pricing, settlement, real-time P&L, monitoring - applications from front to back office on Wall Street.

Why did Thomson Reuters partner with StreamBase for CEP? Initially, they announced four reasons: 

StreamBase in Elektron Brings CEP to Thomson Reuters' High-Speed Cloud

The StreamBase platform lies at the heart of a new generation of real-time, automated applications on Wall Street. As the use of CEP continues to grow, our customers increasingly ask to deploy some of their applications in the cloud. They want their automated processing to happen as close to the exchange as possible for the lowest possible latency, and they want secure and reliable access to their market data.

Thomson Reuters announced that they will provide StreamBase CEP in Elektron, their open, global, ultra-high speed and resilient network for the financial industry. By adding StreamBase CEP to Elektron, Thomson Reuters is creating the industry’s only platform that includes comprehensive real-time and historical data, high capacity network connectivity, managed hosting services, and CEP for rapid application development and strategy deployment.

The First End-to-End Quant Platform for Back Testing, Algorithmic Development and Deployment

Although StreamBase is all about acting on what's happening now, the knowledge of what happened yesterday is essential for any automated system. History is essential to discover trends and patterns in event streams. History is essential to back test automated strategies. History is essential to gain perspective on real-time actions at execution time. Over 90% of applications that use StreamBase also use some form of historical event data management.

Thomson Reuters will integrate StreamBase with the Enterprise Platform for Velocity Analytics, which integrates all Thomson Reuters content, including tick history, reference data, corporate actions, condition code processing and cancellation and correction messages. It also brings together many disparate third party applications including data management solutions, EMS, OMS, price discovery, back testing, trade surveillance and low latency execution capabilities across the quantitative research and trading workflow.

By integrating Velocity Analytics with StreamBase CEP, Thomson Reuters has created the first end-to-end quant platform for back testing, algorithmic development and deployment. 

Thomson Reuters Applications "Powered By" StreamBase

Thomson Reuters will deliver a suite of applications that are “powered by” StreamBase CEP to address low-latency workflow. CEP inside will provide Thomson Reuters clients the benefit of time to market usually associated with turnkey solutions, while at the same time allowing full customizability of the underlying application. One application Thomson Reuters already provides is the real-time surveillance application from Redkite financial which is based on the StreamBase CEP platform. 

StreamBase and Thomson Reuters FX Solutions

The FX markets have rapidly emerged as an important market for the capabilities of CEP. Thomson Reuters announced that StreamBase CEP will complement the existing Thomson Reuters Dealing Aggregator FX trading solution, available exclusively to Thomson Reuters Dealing customers, by providing CEP capability in tandem with the low latency algo trading platform. 

Why did Thomson Reuters choose StreamBase? Mike Powell, Global Head of Enterprise Real-Time Solutions for Thomson Reuters, said it this way: “The financial market landscape continues to evolve rapidly, meaning that nimbleness and time to market have become essential for market participants. Elektron empowers our customers to innovate and achieve high performance through a seamless infrastructure that brings together global market participants, delivers world-class content and creates a suite of new added-value services. The combination of StreamBase’s market leading CEP engine together with Elektron will provide a platform for us to deliver flexible and sophisticated solutions to our customers faster and more efficiently.”

For StreamBase, we’re excited about the vast resources and capabilities of Thomson Reuters can provide our customers. We’re honored to be selected as Thomson Reuters’ CEP platform of choice - their selection validates our focused approach to CEP, the ever increasing importance of the cloud and real-time big data, the disruption of simplicity, and the continued need for low latency and scalability on Wall Street. 

 

Can Innovative Surveillance Be a New Source of Competitive Edge?

In sports, great defense can be a catalyst for great offense. Can the same idea hold true for surveillance - the defense - in the capital markets? This was a question raised by today's panel of surveillance experts at today's StreamBase webinar (watch the replay). 

First, TABB Group's Miranda Mizan assessed the current surveillance market. She described how surveillance is morphing from a defensive obligation to an offensive differentiator, because the markets are changing so dramatically. Mizan argues that the quantity of data, speed of trading, and complexity of instruments have made traditional surveillance techniques insufficient. And since regulation (e.g., MIFID II) is changing so quickly, she argues that firms must re-think their surveillance strategies and technology choices.

Justin Amos joined Miranda. Justin is a former global markets sales and trading executive at JPMorgan, and the MD of Redkite Financial Systems, a UK-based firm whose system called Redeye has been quickly becoming the standard for modern, real-time surveillance systems. Justin described the requirements of today's surveillance systems by describing the motivation for Redeye, which he likened to "anti-virus software for trading."

Together, Justin and Miranda touched on 12 "next generation" surveillance requirements, including:

1. Real-time analytics. Surveillance systems must analyze market data at the speed of automated trading.
2. Historical "big data" analytics. On-line access to trade-by-trade history for investigation, trending, and discovery.
3. Data fusion. Mash-ups of increasingly complex data, including unstructured data.
4. Inclusion of new data sources. The ability to integrate live data, static data, and social media data.
5. Multi-asset class support. Modern surveillance must work across asset classes.
6. Pre-built surveillance algorithms. Standard algorithms like front running, spiking, tailgating, and ramping.
7. Adaptive algorithm modification. The ability to adapt algorithms on the fly to reduce false positives.
8. Alert algorithm extensibility. The ability to quickly add new algorithms to the system as market dynamics evolve
9. Customizable surveillance algorithms. The ability for a firm to tweak an algorithm for their own models.
10. Flexible workflow management and case management. Control over the process of alert analysis, resolution, and tracking.
11. Accessibility for business analyst. With regulation changing so quickly, more firms want their own control over surveillance behavior.
12. Cloud-based or on-premise deployment. The cloud allows more rapid rollout, and may ease global scalability challenges

The panel argued that existing surveillance systems can't handle these requirements. Taken together, the challenge makes what was once traditional "defense," or a compliance function, very new and challenging - a source of differentiation.

Miranda went deeper, with examples of how brokers and the buy side are using modernized surveillance systems: agency brokers are beginning to use surveillance tools to monitor their trading algorithms and optimize their client service and order routing for best execution; the buy side are using surveillance to gain greater control to know that their trading is safe, its orders get to the right places, and that dark pools are working correctly in relation to the rest of the market; sell side institutions are using surveillance tools to institute process and control across the organization, globally, and integrated with automated systems.

Richard Tibbetts, CTO of StreamBase, gave a brief introduction of StreamBase CEP, and why complex event processing is increasingly being used to power surveillance applications; indeed, CEP provides the engine to address many of the 12 modern surveillance requirements set out by the panel.

Simon Townsend, CIO of Redkite, gave a "whistle stop tour" around Redkites' application. He hit on most of the 12 requirements above, and even showed didn't just claim that their algorithms are extensible and dynamic (requirements 6, 8 and 9) - he showed it in StreamBase Studio, and showed how business analysts can extend the Redeye surveillance algorithms.

One of the most exciting times is when a market is transformed by new ideas. In the capital markets, perhaps that innovation is upon us in surveillance, where tools that meet modern trading requirements can turn a defensive obligation into a tool for innovation.