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Stop spoiling the favourite front office child: Optimisation of post-trade operations

By Rik Turner, senior analyst, financial services technology, Ovum

Since the beginning of the global financial crisis, Ovum’s annual survey on the IT investment priorities of capital markets participants has consistently shown back-office optimisation to be among the top three items exercising IT decision-makers in the sector.Rik Turner

That said, post-trade operations – those in the middle and back office – of many capital markets participants, on both the sell and buy side, are in urgent need of optimisation.In essence this means modernisation and automation. Some of the largest sell side firms are still heavily dependent on manual systems, overnight batch processing, and Excel spreadsheets. Ovum believes that the situation that these organisations find themselves in will not to meet the demands of modern-day capital markets.

Even the biggest bulge-bracket firms, which may have already automated a lot of their post-trade processing, would have done so for a product set that is slimmer and simpler than what they will soon be required to handle. This is largely due to regulation around central clearing and exchange trading for over-the-counter (OTC) derivatives and liquidity risk management (LRM).

Furthermore, they will frequently have silos of post-trade systems with, for instance, a different reconciliations platform for each asset class. This is clearly not going to be an optimal post-trade situation, given their desire to explore multi-asset class strategies and the need to calculate and address liquidity risk across the entire enterprise in a timely fashion.

There is a clear technology gap between the front office, which, as the locus of revenue generation, has enjoyed “favourite child” status with regard to IT investment for many years, and the middle and back office. The time has come for investment in post-trade. If operations are to cope with the next wave of market and regulatory development it can no longer be ignored.

The front office has enjoyed significant investment in technological sophistication
As the place where revenue is made, the front office has always been the main focus for IT investment. This has particularly been the case during the last two decades, as deregulation has led to fragmentation of liquidity and the development of technology-basedtrading strategies to exploit this situation. The technological leap forward that the front office has taken, and continues to take,means the back office must now be far more automated and optimised if it is to support further advances in trading strategy.

With margins on cash equities in the mature markets increasingly slimming,market participants have also begun to look at new trading venues and asset classes, as wellas developing more complex strategies. These involve different asset classes in the same tradefor hedging purposes. All this puts additional stress on post-trade operations, which need to support new identifiers and the processes required to trade in new asset classes.

It is also good business practice to optimise post-trade operations at a time when the overall world economy is in the doldrums. This could be to drive down cost, improve time-to-revenue by freeing up more stock for repo operations, or simply to attract customers by highlighting the ability to handletheir business in a timely and efficient manner.

‘Repooperations’ refer to a form of short-term borrowing, originally for dealers in government securities and now used increasingly for other asset classes too. The dealer sells the government securities to investors, usually on an overnight basis, and buys them back the following day. For the party selling the security and agreeing to repurchase it in the future,it is a repo; for the party buying the security and agreeing to sell in the future, it is a reverse repurchase agreement.

Better post-trade operations can also lead to better customer relations. Buy-side firms have moved to more multi-broker strategies in the wake of Lehman’s sudden demise, so streamlined post-trade operations can help a sell-side firm stand out inthat crowd. Buy-side firms may also look to their brokers to perform a lot of post-trade processing on their behalf. This means there is also an additional revenue opportunity in running the most efficient post-trade operations.

By carrying out LRM on an intraday basis, institutions will not only be able to comply withthe Basel III requirements enshrined in a growing number of national laws, but also to gain a real-time view of their risk profile. This, in turn, will inform them of what stock or other instruments they have that can be lent to other market participants on a fee-paying basis, without jeopardising their own exposure levels.

In addition to the operational requirement, there is also the need to meet the increasingly stringent compliance requirements of regulators across the globe. A company’s ability to carry out appropriate risk management, and clear and settle trades in asset classes that were previously not centrally cleared, is becoming mandatory.

Choosing the appropriate optimisation strategy and measuring success
The majority of post-trade functions were automated initially by being encoded into software for deployment on the user’s premises. The companies that produced this software usually started by offering it on a server-licensing basis but they are increasingly moving into service delivery. Some can now manage the software deployed on a server ona customer’s premises, or offer an entirely cloud-based managed service with a customer simply accessing the service through a web browser. A customer’s choice will depend on a variety of factors, including its technological prowess and available resources, but also how it is evolving its business.

Since the basic ethos behind implementing a reconciliations platform is to automate the process as far as possible, with only exceptions to be handled manually, a key metric for deciding how well your firm is doing on this front is the auto-match rate. This measures the degree to which trades are being matched and confirmed automatically, without the need for human intervention. If the rate drops too low, further optimisation is required.

Rik is a senior analyst on the Financial Services Technology team, focusing primarily on the financial markets area and, in particular, on capital markets infrastructure.