By Theo Hildyard , Software AG
@theohildyard

Continuing on the theme of my previous blog post, which looked at how firms are starting to use in-memory data management technology to perform complex calculations on large data sets ‘on the fly’ – such as real-time credit valuation adjustments (CVA) and pre-trade capital adequacy calculations – let’s now take a look at how banks can use this ability to their advantage in the FX markets.

But first, let’s take a step back. A bank – particularly a large tier one & tier two investment bank – is an incredibly complex beast, made up of multiple business lines across numerous geographies, performing a range of functions, the common element of which is that they all involve the flow of money. So every one of these business lines has a constantly changing exposure in one or more currencies.

Traditionally however, each of these business lines has operated under its own ‘silo’, with its own systems, data models and reporting regimes. Typically, one siloed business unit would not have visibility into the currency exposures of another. This of course could be perfectly valid due to Chinese Wall-type situations, after all not all areas of the bank need to know – or indeed should know – what is happening in other areas.

From the overall perspective of the bank however, silos are inefficient. Particularly given that banks need to have a centralised view of currency exposures across all business units not just for the purpose of regulatory reporting around capital adequacy, but also to effectively manage overall currency risk. The faster the bank can ingest and analyse all the necessary data to calculate that centralised view, the more effectively it can manage that risk.

Now consider the fact that at least one of the business units of the bank will be acting as a liquidity provider in the FX markets, offering two-way bid/ask prices in various currency pairs out to customers and counterparties, either through its own single-dealer platform or through one of the many multi-dealer platforms that operate in the market.

Without real-time visibility into exposures across all of its business units, the bank is immediately at a disadvantage when making these two-way prices. If it doesn’t know – from a firm-wide perspective – whether to increase or reduce its exposure in a certain currency, the bank is opening itself up to unnecessary risk.

If on the other hand the bank is able to not only perform real-time netting of currency exposures across all of its business units – but also to factor in the results of on-the-fly capital adequacy calculations to give a true picture of its balance sheet at any moment in time, the FX trading arm of the bank can effectively “skew” the prices it offers out to the market, adjusting bids or offers to be more or less aggressive to take into account whether it needs to go longer Euro versus the Dollar (for example) to stay balanced from a capital adequacy and balance sheet perspective.

From a technology perspective, this kind of real-time adjustment and weighting of prices based on capital adequacy is certainly achievable today. Components such as in-memory data management, complex event processing, streaming analytics and ultra-fast messaging, when employed together, are giving banks the ability to be much more pro-active in the way they manage their cross-asset, cross-geography and cross-business exposures than ever before.