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Optimising FX P&L: How Smart is Your Data?

Traders Magazine Online News, March 21, 2019

It's little secret that FX businesses in many banks are struggling for profitability and adequate ROC. Coupling this with increasing regulatory data management requirements further darkens the picture. However, as Jack Jeffery - Chairman of Mosaic Smart Data and Matthew Hodgson Founder & CEO of Mosaic Smart Data - explain, there is actually a major opportunity implicit in this situation. If done well, compliance with data regulation can also be used to boost an FX business's profitability and automation.

Regulation: drawing opportunity from necessity

The past few years have seen a raft of legislation, such as PSD2 and GDPR, that directly affects the banking industry. A significant proportion of this regulation includes regulatory requirements specific to data, with one example being the BCBS 239 standard within Basel IV, which requires banks to meet specific standards relating to risk data aggregation. However, despite the deadline of January 2019, progress has been slow - a point that has not been lost on regulators. The ECB's May 2018 Thematic Review made clear its displeasure[1], while the BIS has encouraged national supervisors to apply more stringent measures, such as capital add-ons and restrictions on business activities, to banks that fail to comply[2].

Jack Jeffery

Compliance with this (and other) data-related regulation is clearly not optional. However, if undertaken in the right way, it is also possible to derive major business benefits at the same time. This applies across the banking enterprise in general, but is particularly relevant in FX businesses, where extreme cost pressure is now the norm and profitability is depressed - both of which are driving a need for automation.

The critical point is how data is managed and stored. An ideal implementation is one where diverse data classes and formats become completely clean, consistent, normalised and enriched. In addition, this capability has to be channel-agnostic and apply (among others) across electronic, voice, direct, prime broking, retail and corporate activities.

Apart from achieving regulatory compliance, this opens the door to converting clean big data into smart data: in this case, smaller information subsets that are both valuable and actionable. This data will then be accessible from multiple perspectives, such as individual client activity by pair, by channel, by request, by deal, by instrument, by hit rate and so on.

Democratising knowledge in real time

Assuming a smart data solution with robust entitlement controls is implemented, it becomes possible to provide each user with access to precisely the data and analytics they need to execute their role more efficiently. Furthermore, if the solution is also structured to be open, then in addition to its own analytics it will also be possible to integrate proprietary analytics and tools developed in- house. Users will therefore potentially have access to best in class internal, external and alternative data sources and analytics.

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