Trading Functionality: Price Engine Developments
Recent research has highlighted the fact that the needs of customers for advanced trading functionality will mean high costs for banks over the next few years. Significantly, the sell side’s technology spend of around US$400m annually on e-commerce components will nearly double by 2010. In addition, while the proportion of client volumes traded electronically is currently approximately 50 per cent, this is set to increase to around 75 per cent by 2010 when the FX market is expected to see volumes of US$3 trillion a day traded, according to ClientKnowledge, a wholesale finance market research company.
End-users will increasingly demand the ability to deal with one click on guaranteed prices wherever they wish to trade, be it directly from their bank’s proprietary FX trading desk or via a multi-bank portal. The move towards streaming pricing and clients’ requirements to be able to trade from multiple locations are just two of the driving forces behind banks reconsidering their pricing offering.
As a result, over the last 10 years the foreign exchange market has evolved to the extent where many banks’ pricing engines are no longer adequate for them to remain competitive. Upgrading and adapting pricing engines to meet the demands of the marketplace is currently a priority for many financial institutions.
A brief consideration of the historical development of FX pricing engines demonstrates the fact that many banks have been slow to respond to the movement of the market. Little more than a decade ago, dealing via telephone was widely replaced by online trading. Automation of the front end, however, usually wasn’t matched by an upgrade in the automation of price discovery. In most banks, both systems have largely been based on request for quote (RFQ) technology where a price is generated on a demand basis, and then held for a period of time before a new price is generated in response to a customer enquiry.
The advent of online portals, such as FXall, created the need for banks to provide streaming prices. Most banks, however, responded to this by creating what appeared to be a stream from the dealer side based on RFQ information. Thus, though the front-end appears to be current, it is actually driven by outdated processes. As a result, RFQ price engines have become stretched beyond the task they were originally intended for.
The explanation for the huge technology spend banks are expected to make does not stop here. The attack on banks’ competitiveness is happening on a number of fronts. These include speed of distribution, accuracy of pricing, integration strategies and meeting the needs of new and emerging customers. First and most importantly, there is the need for speed. Banks need to be able to provide executable prices faster to a variety of trading channels if they are to offer a better and more efficient service to clients. Linked to this is the need for accurate pricing: black-box driven algorithmic trading models enable margin traders to take advantage of arbitrage opportunities created by ‘off-market’ prices in seconds. A robust ‘bank rate’, which is constantly changing to reflect market conditions, is a bank’s best defence against opportunist traders.
In fact, professional traders and in particular margin traders are a rapidly-growing market for banks, though few of them have harnessed technology to efficiently meet the specific needs of different client groups, especially those that are newly emerging and whose demands are still evolving. Many banks currently have a variety of disparate systems with which to service corporate, retail and internal customers.
Finally, banks need the capacity to deal with increased volumes; ClientKnowledge predicts volumes to exceed US$3 trillion by 2010. Competitive pricing engines used by early adopter banks can lead to increased volumes from new clients as well as those who have been serviced by disparate areas of the bank, for instance, wealth management, treasury and/or prime brokerage. A consolidated bank-wide pricing engine should enable these businesses to be serviced from a single electronic platform. This platform does need to be highly scalable though if it is to cope with vastly increased transaction volumes.
Banks that have been slow to update their pricing engines have experienced pain in the open market – either resulting from the distribution of ‘off-market’ prices, or because they have been slow in comparison to true streaming rates and have lost out on business. On top of this, banks have found that the cost of dealing with its own customers has increased in line with the number of available dealing channels.
The answer to this conundrum is the development of true streaming models that distribute live, executable prices from the beginning of the trading process. Furthermore, changes in market conditions are reflected in the prices distributed by every one of the bank’s dealing channels with next to zero latency.
While true streaming prices are essential for the safe and efficient servicing of clients, it is important to note that the RFQ model is still highly relevant to many customers. It must be said, however, that adapting a true streaming model for RFQ use enables clients to benefit from true one click pricing rather than from a bank continuing to use an RFQ engine to provide a customer-facing veneer of ‘streaming’ prices which isn’t backed up by sophisticated protective tools, i.e. the ability to automatically pull out-of-date prices in volatile trading conditions.
Investment will also pay dividends as the forward march of the non-FX markets demands greater automation, and as pricing non-FX instruments becomes easier and quicker to achieve. In addition, white label models have placed the downstream bank at a disadvantage in terms of being dependent on a single liquidity provider. Using a true streaming model enables a number of banks to become liquidity providers, as well as the downstream bank itself feeding liquidity into the system, e.g. its local currency.
The current competitive situation for banks is one of opportunity and threat and the example of margin trading is a good illustration of this. As noted earlier, the rise in opportunistic margin trading offers a good business opportunity for banks. However, the irony is that banks have to simultaneously protect their own desks against margin trading activities in the marketplace while offering sophisticated tools to attract this business.
For end-users, this is a time of opportunity – as banks struggle to meet the needs of the most sophisticated trading outfits, all clients are likely to benefit from the extensive investments banks are making in their pricing capabilities.