By John Mitchell, Vice President, Asset Control
Financial institutions have spent the last four years getting rid of the hangover that toxic assets created in 2008. While the industry might be tempted to give itself a clean bill of health, not enough focus has been placed on cleaning up internal processes – namely data management – to support these assets. With data volumes and risk management needs quickly outpacing the capabilities of legacy processes, it’s time for these institutions to flush out any toxins lurking in their data management.
When discussing toxicity in the context of data management, we’re referring to the antiquated processes that have been created to support trading and investment management as they have rapidly expanded in size and complexity over the last decade. The speed at which the markets have moved, and the need to deliver better pricing and risk management, has meant that financial services firms have relied on quick data fixes in an attempt to maintain their data management operations.
These quick data fixes and the rapidly expanding data footprint within financial services organizations have led to data management models that are too inflexible for today’s needs. One approach – the creation of a single monumental, monolithic data management structure designed to deliver a single view of the “truth” – is extremely inefficient and ignores the fact that multiple golden copies are required. Another approach – sourcing data individually by each system, business unit or asset class – leads to duplication and chaos. Both approaches often increase operational costs, counteracting executives’ efforts to pare budgets.
To deal with greater operational demands, data management needs to be more athletic: strong but agile, flexible but resilient. Now that the industry has worked hard to rid itself of toxic assets, it must work to remove the toxic data structures that supported them. 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 detox to purge their workflow of excess bulk and dangerous toxins.
This is what modern data management is all about. It requires buy- and sell-side firms 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 approach that a medium-sized asset manager should take is very different from the approach needed by a global custodian with thousands of customers, tens of thousands of employees and hundreds of billions in assets.
In the same way, individual business units, product lines and investment strategies all will 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.
The key is to ensure that everyone can 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.
This ability becomes even more crucial 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.
Slimming down the data management structure is not a seasonal fad or a crash diet. If financial services firms want to detox their data to optimize their operations and decision-making, then a sustained – and sustainable – approach to managing information is required.
If not, data management – which should be the lifeblood of any financial institution – risks becoming a cause of almost fatal sclerosis.