Automating operations on mission-critical data
Part one of a two-part series
Hello everyone and welcome to the latest edition of GreySpark Insights.
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Post-trade operations departments in major financial institutions are beehives of activity, but unlike bees, middle- and back-office teams are not perfectly coordinated and aligned to one cause. Yet, those teams are critical to the operation of capital markets firms, both in terms of economic performance and risk exposure. In an environment with multiple trading partners, diverse data formats and interconnected software systems of different types and tenures, post-trade processing is non-negotiable.
However, professionals in the middle- and back-office can be seriously ill-equipped to carry out these important tasks. Operations workflows tend to rapidly multiply, grow in complexity and become riddled with idiosyncrasies. The results are pervasive duplication of effort, additional costs and, more importantly, increased risks of error.
Middle- and back-office personnel are typically organised into dedicated teams aligned to specific functional, asset-class and/or regional lines, and rely on a wide array of systems for both data sourcing and workflow execution. While the data they ingest, analyse and output again is used by multiple departments and even exchanged with external parties – such as market infrastructure providers, clients and regulators – the technology to manage it is often selected and deployed on a per-team basis. Spreadsheets proliferate wherever there are gaps in the technology stack, especially in manual or semi-manual data processing for bespoke products (for example, OTC derivatives) and processes that rely on the data on such splintered systems over time degenerate into siloed, labour-intensive and error-prone workflows that serve only to create cost, delay and risk.
Consequently, with an ever-increasing number of internal and external data handover points, many institutions find themselves operating a giant data management facility without central control and visibility. Skilled middle- and back-office professionals are spending their time clearing break notifications and waiting on their IT departments to fix technical blockages, instead of doing higher-value work. Even at this high cost, getting a clear view of the right data at the right time often remains elusive.
It’s a problem that hangs over several financial institutions, and one which illustrates the need for more advanced, enterprise-wide, data-centric operating models.
Thankfully, this model can be achieved, and it points to a “coming of age” of data management infrastructure in capital markets.
Later this week, we’ll be sitting down with Meri Paterson, manager of GreySpark’s fintech advisory team, to find out more about how middle and back offices in financial institutions can tackle their data pain points outlined above. Stay tuned.