Disparate markets and complex trading call for smarter exceptions management, argues Donal O’Brien, business development director of Coexis.

If Societe Generale’s reference data systems had been a bit wiser to the activities of its users, could the actions of Jerome Kerviel and the French bank’s subsequent £3.7bn loss have been avoided? The need for increasingly complex interactions between central reference data and distributed transaction processing systems is driving many banks and brokers to re-evaluate their processes. But it’s only through the application of intelligent exception management, sometimes known as straight through exception processing (STEP), that they can really grasp the nettle.

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Listen up compliance officers. Your life is about to get trickier. You’re about to be bypassed. You might as well throw in the towel now. Sure, you can keep hold of all those corporate emails and instant messages, lock down the desktops of your employees and block their access to websites, but in this increasingly mobile online world it’s going to be pretty impossible to keep control of your flocks and how they interact in the 2.0 cyber world.

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Long the heir apparent to his predecessor Lenny Schrank, Lázaro Campos has finally taken the helm at Swift. Here he tells A-Team IQ how he plans to build on its franchise to better meet the needs of its customers in the securities industry

By Thea George

When we meet Lázaro Campos at Swift’s La Hulpe headquarters in August, he recalls that he received the news of his appointment as the co-operative’s new CEO on a Tuesday. “I was just about to give a presentation to 400 people,” he says. “I didn’t tell anyone at the time, except my wife.”

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With the exponential rise of algorithmic trading in the US and European markets seemingly affirmed, how far beyond equities and into the Asian markets can it go?

By Roger Aitken

The use of algorithmic trading strategies has grown rapidly in Europe during 2006 and into this year. An Edhec Risk Advisory survey revealed recently that 78 per cent of buy side firms were using algorithms, versus 58 per cent in 2004. Certainly, more firms have access to algorithmic trading systems, yet it appears that they still only use them for a small percentage of trades. Edhec’s preliminary survey findings highlight that algorithm deployment among European buy side firms accounted for just three per cent of business, compared to 11 per cent for direct market access (DMA) and 17 per cent for programme trading.

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A couple of weeks back, the UK rock group Radiohead put its latest album up for sale on its website (ingeniously on a “pay what it’s worth” basis) and the demand was so great that its website promptly crashed. Nice idea guys, shame about the execution.

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More and more companies see service-oriented architecture (SOA) as a strategic imperative that can transform business operations, delivering flexibility and agility, a more cost-efficient IT organisation and improved alignment of IT to business goals. But for such a major initiative, it is surprising that more focus is not placed on its impact on business risk. If a company is going to go to the trouble of not only putting in place the infrastructure and project budgets to deliver SOA, but also to tackling the organisational and procedural transformation required to optimise SOA benefit, surely it is worth considering the risk implications.

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This column is being written in San Francisco. I’m in town to attend the second running of the Office 2.0 conference, which kicks off tomorrow. It’s very much a Silicon Valley event - vendors, venture capitalists, lawyers and maybe even a user or two. But with 500 plus paying delegates and a host of sponsors, the buzz is already mounting. All the delegates were given an iPhone (to keep) as part of a collaboration experiment (I am collaborating by sharing a special iMix music playlist that I programmed for the event).

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Wherever I go these days, I hear the term “carbon footprint”. Being environmentally conscious is a new checkmark on the scorecard of most global companies, including those in the financial markets.

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Escaping the mayhem of the recent SIFMA trade show at New York’s Hilton, I walked a few blocks to the trendy Dream Hotel, to view a demo of technology that could not only redefine desktop deployments, but also give a boost to grid computing.

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Most would agree that open source technology can drive down costs of implementation and support, although many say this misses the bigger picture of open source adoption. To them, the rapid deployment and innovation that open source offers are the real benefits.

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It’s the biggest story in the market data business. So why doesn’t it feel like it?

The answer probably lies somewhere in the surprise factor in Thomson Corp.’s £8 billion offer to acquire Reuters, in the ‘reverse’ nature of the proposed deal itself, and in the fact that most people in the industry – though they may not acknowledge it – are held in a kind of awe at the cleverness of the proposed arrangement.

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In A-Team’s latest research, Faster Than a Speeding Bullet – Low Latency Architectures and Building Blocks For Tomorrow’s Trading Applications, we made some predictions, and one of them was: “Basic functions such as datafeed handlers, in-memory databases, messaging middleware and data fabrics will become increasingly commoditised.”

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To many on Wall Street, mention open source and they will immediately equate it with Linux. There’s no doubt that the open source operating system has been a big hit in the financial markets. It was in the right place at the right time as firms were looking to write off their investments in expensive Sun boxes and replace them with cheap x86-based blades.

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When one thinks of technology suppliers in the SOA and Web Services world, it’s names of heavyweights like IBM, HP, BEA and Microsoft that spring readily to mind, followed perhaps by the upstarts, such as WS02, Active Endpoints and Parasoft.

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As Service Oriented Architectures have become increasingly in vogue for building applications, attention has turned to the tools that might be used to create and deploy them.

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In the old days there was middleware. The likes of IBM and Tibco made a fortune from selling products to Wall Street to integrate disparate systems, to hook up front and back offices, connect to clearing houses, trade with customers et cetera.

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