An Operational Spring Clean Begins With Data


Operational processes at financial services firms could use a spring clean. Over the last few years, financial institutions have clung onto outdated data management structures to support trading, portfolio management, compliance and risk management. As a result, the financial system has a significant number of toxins within its assets, operations and, down at the core, its data. Unless action is taken, financial services firms risk becoming akin to hoarders, where mountains of clutter threaten to engulf the people around them.

In data management terms, toxicity can be described as the vestigial data processes that have been built to support the very complex and global businesses of trading and investment in the last decade. The problem is that for many institutions the sheer scale of data management has created monumental, monolithic data management structures that focus on delivering a single view of the truth when in fact multiple golden copies are required. The alternative, of having data sourced individually by each system or business unit or asset class, is no better.

When you consider how fast the markets, and now the regulators, can move, the need to deliver pricing, risk management and compliance mechanisms in a timely manner has meant the industry has relied on quick data fixes. The result is that data management often resembles a Heath Robinson-style machine, made up of supposedly temporary fixes, unlikely appendages and redundant mechanisms. As the clean up from the global financial crisis continued, it became clear how inefficient these haphazard methods were at managing the risk across the financial markets.

The industry is working hard to rid itself of the toxic assets that caused the markets to all but collapse, but it must also work to remove the toxic data structures that supported them. Times have changed since the crisis hit – an increased regulatory burden, greater demands for transparency and a more complex operating environment has meant an exponential growth in data volumes. This has put much greater demand on the infrastructure that supports financial institutions at a time when austerity governs most operational budget considerations.

The problem has been exacerbated as requirements for pricing, risk management and compliance creep closer to real-time. These types of processes, once confined to the middle and back office, are being adapted for the front office to provide, for example, real time scenario analysis and curve construction.

All of this requires rapid data processing and analysis. However, instead of piling on more infrastructure, adding new universal feeds, expanding data warehouses, or putting new terminals on every desk, financial institutions should be considering a data spring clean to purge their workflow of excess clutter and dangerous toxins.

In fact, this is what modern data management is all about. It requires financial institutions to look carefully at the data they need and how it will be used. Any data management infrastructure has to be appropriate for the size of the firm and its individual operations. The solution that is right for a medium-sized hedge fund is very different from the solution needed by a global custodian with thousands of customers and tens of thousands of employees.

In the same way, individual business units, product lines and investment strategies will all require different data sets, and will consume them in different ways and at different times. Where traders want data on actual holdings, analysts use it for modeling ‘what if’ scenarios.

by Mark Johnson, Vice President, Global Sales at Asset Control

The key is to ensure that everyone can make sense of, and meaningfully use, the increased information required from them and available to them. That requires a central, streamlined system that has the ability to consolidate, cleanse, and distribute data, and the know how to know where and when it’s supposed to go.

In essence data management should support the organization, not smother it. With financial institutions under greater pressure than ever before to enhance their risk management, compliance and reporting capabilities, first they must clean up their data. However doing so should not be a seasonal fad. If financial services firms want to spring clean their data to optimise their operations and decision-making, then a sustained – and sustainable – approach to managing information is required.

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