LondonAccord:Green Finance

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Green Financial Services Industry

If financial services accounts for around 8 percent of global GDP, and Information and Communication Technologies (ICT) account for about 4 percent of total energy consumption, then the financial services industry is responsible for at least 0.32 percent of global carbon emissions. Call it 0.5 percent, given the industry’s fascination with and intense use of ICT. A reasonable target is to reduce electricity consumption a bit, but many climate change analyses talk of impact reductions in the order of 80%, i.e. reduce consumption by four-fifths. A 2009 report by SAMI Consulting for the City of London pointed out that finance's growing ICT intensity made future power supplies the City's major infrastructure problem[1].

One change underway is roving grid computing for heavy MIP (million instructions per second) applications. Value-at-risk (VAR) or portfolio optimization applications could be dynamically scheduled to run where carbon emissions are lowest. Smart grids and energy sourcing strategies mix. A New York bank could take advantage, for example, of cheap French overnight nuclear (low carbon) power or Danish wind energy. As carbon and power markets converge, roving processing correlates with low power prices.

A second change is to optimise the efficiency of applications and operating systems. Reduce MIPs. Today’s ICT departments can easily and materially reduce usage through simple expedients such as software that shuts down unused machines. However, years of organic growth have resulted in grossly inefficient ICT infrastructure that requires replacement. ICT departments have been profligate with scores of unused features now lurking on desktops, gobbling processor time and energy, waiting aimlessly to be called into action. Computational efficiency used to be a badge of pride among assembler programmers. Project managers, systems analysts and programmers can radically reduce MIP usage through redesign at all levels - applications, middleware, operating systems, hardware and grid.

Of course, reducing MIPs also reduces latency, so a third, more radical change would be to challenge the excessive importance of latency itself. Low latency, with its knock-on implications for market data rates and gross power, has been on the agenda of buy and sell side firms for a few years. Today multi-lateral trading facilities (MTFs) and suppliers talk about "ultra low" latency. By co-locating servers close to exchanges, banks, investment managers and traders subject themselves to local power sources. Financial services firms need to rethink markets. Can we redesign markets so that traders using an Icelandic geothermally-powered, low-carbon emission server farm trade on equal terms with a London-based server farm near the London Stock Exchange’s server farm running on electricity produced by a coal-fired power station? Should the London Stock Exchange server farm be based near New Zealand geothermal energy?

Financial services could break loose of latency binds if firms convinced exchanges to use periodic auctions every few seconds, easing today’s latency pressures by several orders of magnitude. Most algorithmic and time-sensitive trading occurs in a limited number of typically highly liquid instruments. On the London Stock Exchange, it’s a score of stocks led by Vodafone. Periodic block auctions have attracted academic interest as exhibiting potentially more efficient allocation, pricing and efficiency across the market, as opposed to existing simplistic "first-in, first-out" models. There are numerous variations on periodic auctions that deserve examination. As buy-side firms, sell-side brokerages and exchanges trumpet their environmental credentials, it seems hypocritical to structure markets in environmentally damaging ways when there might be more environmentally benign structures that also equate with more efficient markets.

Roving processing and energy sources, slashing MIP requirements, and redesigning exchange architectures will all matter when seeking an 80 percent reduction in environmental impact.


Michael Mainelli, "Green Data: Impact Versus Low Latency?", Inside Market Data, Volume 24, Number 32, page 9, Incisive Media Limited (11 May 2009).

Interesting article about a Verdantix report praising cloud computing as cutting emissions - - and the report itself -

"Koomey's Law" related to Moore's Law, that we can expect comparable improvements in IT energy efficiency -

Long Finance Discussion -

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