By implementing the STTP, banks can smart route clients' orders to different venues according to rules that enable the bank to define and deliver its "best ex" policy.

According to Harry Gozlan, CEO at Smart Trade, "we can simulate savings generated by market participants - buy-side, sell-side and broker - by running the smartTrade Trading Platform simulation locally in live conditions or through an ASP. By applying various conditions to incoming orders and hedging scenarios, banks gain an accurate picture of the risk-reward ratio of internalization or crossing that can be achieved, measuring economic savings generated through internalizing, including keeping the bid/ask internally and eliminating execution and clearing fees. This simulation can also profile categories of order flows - retail, institutional or professional - pinpointing what type of flow can match against other types. Another benefit gained through this fast-to-implement STTP simulation system is that it's very similar to the actual STTP production system, facilitating a fast, efficient move into production."

According to TABB Group in its December 2006 research note, Liquidity Management: Pushing Automated Trading beyond Agency Brokerage, liquidity management, the next phase of electronic trading as customer-flow and order-flow tools are now widely adopted, is the methodology surrounding how firms automate their trading desks. This includes rules around valuation and pricing of liquidity, handling of customer order-flow, matching of internal liquidity and automated rules and methodologies around provision of capital for internal market-making and proprietary trading.

A liquid market, says TABB Group, regardless of asset class, relies on three components to be successful: tightness in price (bid/ask spread), depth and resiliency. Although liquidity management is not a new concept to banks, until recently most banks have not fully automated this process. Algorithmic trading and market fra fragmentation have now changed this situation due to the sheer volumes and speed of the transactions. Reg NMS in the US and MIFID in Europe propel the need further, especially MIFID, whose directive is cross asset for best execution.

Regardless of size or location, banks face serious challenges in building the automation for liquidity management, primarily around multi-asset trading, because an internal market needs to be created to know what your depth of the market is. Explains Gozlan, "Products cannot be easily 'combined' to create this internal market as each one has their own unique characteristics and the model is not scalable, especially for synthetic products."

Smart Trade addressed this issue by building its STTP platform as an asset-agnostic platform. From a technical perspective, says David Vincent, CTO at Smart Trade, "the STTP has been developed using object-oriented methodology and built on a component approach. Each component can be extracted from the rest and replaced by another one via the Spring Framework." The platform, he explains, has two engines; the execution engine, which enables multi-asset trading via its mathematical representation of the environment; and the routing engine whose function it is to decide the final destination or destinations of the orders, quotes and indicative prices.