FINANCE

EARLY DETECTION OF MISMATCHED TRADES IS KEY TO MANAGING RISK AND MAXIMIZING PROFITS ON THE P&L DESK

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Simon Richards, CEO USA, Fonetic

Simon Richards

Simon Richards

A brand new financial technology category – solutions for the management of the P&L trading desk – is being born. The need is clearly evident: imagine a fast moving trading floor where, unsurprisingly, mismatched trades are a common challenge. The rub comes when a trade booked for $10m is tallied against the actual trade (completed on the phone or by chat) which is booked at $100m – it is a scenario that is often not detected until reconciliation when the damage is done and the chance for immediate remedial action lost. In a fast moving market, the consequences of these kinds of mismatched trades for banks, brokers, financial institutions and independent advisors globally are costly with millions of dollars lost on the desk’s P&L.

The problem lies in the time it takes for the mismatch to be identified and unravelled. For example, a trade made on x date follows the scenario above, with the broker thinking the sale has been made for $100m but the trader thinking the buying volume was $10m. Three days on from this (trade date +3) the clerk in the trader’s Back Office finds the anomaly and calls the broker’s Back Office. Both parties agree there is a mismatch and proceed to try to find all the communications relating to the trade that will show where the mistake was made. This can take around a week (trade date+3+7). Once all the information is found, both parties then have to unravel all the steps of the trade in order to identify if the mistake was made by the broker or by the trader. This can take another five days. So the whole process of sorting out the mismatched trade can take from day trade date+3+7+5 = 15 days. And here’s the crucial bit – in 15 days, markets move and this is when the millions of dollars can be lost because the correct trade must be booked at the trading price. Furthermore, not only is the bank or firm that made the mistake liable to make a loss, there is an impact on their trading book. Undoubtedly, mismatched trades cause a ripple effect that goes way beyond the original trade that didn’t match up.

What the industry has been crying out for is a technology solution that enables banks’ Front, Middle and Back offices to enable the better management of the risk associated with the P&L of a trading desk. A massive part of this is ensuring the fast and early detection of mismatched trades as herein lies the P&L risk. However, before risk can be measured it needs to be quantified and the only way to measure trading risk is to fully analyse all communications that reveal trading behaviours and then decide what to do with it. For the technology to really deliver, it must have the ability to understand what is said in all communication and, more importantly, when the trade has been concluded in a voice call. To be really first class, it should be able to report the early detection – the benchmark is within 15 minutes – before market movement drives greater losses, enabling swift remedial action and mitigating large losses.

What is required is a linguistics-based trade matching solution that can automatically process, analyse and match voice and text communications with their corresponding trades, utilising trade data and metadata in addition to the content of the communications – even when the content of the conversation is along the lines of “Hi how are you? Mine.” You need many different elements to come together including social media, data analytics, sentiment analysis and unstructured data in order to create a single multi-channel, multi-language solution that can decode trader behaviour and then make recommendations on how to manage risk. Most importantly, the technology must be able to analyse the context of the voice content so that it is possible to establish accurate meanings right from the start of the data gathering process. This takes more than an understanding of trading specific language and slang. It also requires experience and understanding of the trading floor environment. For example, the word ‘strike’ is often used in the context of trades but it is also a word often used in sport – any analytics of worth must be able to spot the different uses. What is needed is a solution that goes beyond who’s talking to whom and how often. A relational picture must be built up over time that allows the analysis of all the types of communications put together as well as the people involved. Only then will context anomalies show up. However, this level of insight is not possible from speech-to-text or phonetic technologies. It requires speech recognition ability that is able to monitor, capture and understand the entire data set – what is said in every voice recording, email, chat and IM – so that it is possible to understand what is really happening on trading floors in all languages to a very high level of accuracy.

More than ever the financial community needs a technology partner it can rely on; one that helps to eliminate wasted time, unnecessary errors, misdirected effort and not least, money lost through mismatched trades. The smart money arms itself defensively by seeking a technology partner that can enable it to properly manage risk, providing peace of mind and freeing it to get on with trading. Dare I say the advent of this new category of financial technology – management of P&L risk – will herald a new era in banking that discards so call ‘dodgy’ trading to one that embraces creative trading?

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