By Jennifer McMackin
Many investment managers’ trade reconciliation and other post-trade processes are still burdened with the inefficiencies of collecting, normalizing and validating data from third-party sources. A typical investment management firm receives numerous data feeds on securities, positions and transactions. This creates more work for operations teams to manage data and maintain provider links, while causing workflow and settlement risk and delays due to errors and manual effort.
Is this the best way to acquire and aggregate external data, and utilize your staff’s time and resources? Is your firm potentially missing out on opportunities to optimize processes and spend more time on strategic areas? Let’s explore the two main data aggregation challenges investment managers face and what they can do about it.
1. Inefficiencies of Manually Collecting Data
Locating the best data feeds aligned with a firm’s specific data requirements can be challenging and time consuming. Many data sources have report libraries and may offer numerous report options under a variety of categories. One data source may provide as many as 15 different holdings reports to choose from, requiring staff to spend time to review and understand the specific data elements each one contains.
Once choices are made, the next step is to initiate connectivity with each data supplier and retrieve specific reports. This is challenging as well, as data is coming in at various times, in many different formats and there is no easy way for staff to validate the data. Data files must be aggregated, normalized and validated for use with internal systems and downstream processes like portfolio accounting, reconciliation and settlement, performance measurement, compliance, corporate actions, collateral management, and securities lending.
Manual processing of data is not only inefficient and prone to errors; allocating existing operations staff to collect data takes away from their ability to focus on higher value tasks. In addition, the data aggregation process does not stop with setting up and receiving data feeds. Because format changes are almost always unannounced, and tokens and passwords expire regularly, each feed and data supplier must be closely monitored and managed – including changes to tokens, passwords, formats and agreements – to ensure consistent access to data sources, such as custodians, prime brokers, and fund administrators.
2. Risk Due to Data Quality, Delays and Staff Turnover
Many data feeds provide a limited set of data points, and files from data suppliers can go missing or contain errors at any given time. Identifying incorrect data and locating the correct files is a manual, time intensive process. If the data acquisition role is not staffed at all times (which it is usually not), process delays and risks will ensue if data delivery issues are not quickly addressed.
The process of managing data feeds, tracking down missing data, and adjusting systems and workflows to changing file formats requires ongoing attention from operations staff and often times, technology. Many team members also lack internal knowledge of data collection and normalization processes, or the specific knowledge resides with one or few people within the firm. This places the firm at risk of that acumen leaving the firm whenever there is employee turnover.
The Solution: A Proven Data Aggregation Service
The notion of organizations focusing their most valuable resource – people – on value-added work, rather than routine or commoditized tasks, is nothing new. Specialists have stepped up to the plate to take on the work that firms deem less strategic and best left to reputable service providers. In the investment management space, data aggregation is more critical than ever, as more regulatory requirements emerge and settlement timelines shrink. Using a comprehensive, outside data aggregation service can enable firms to acquire data in a secure, reliable and auditable way, allowing them to share information across business lines seamlessly.
What should you look for in such a service? For one, it should be staffed by people who have the appropriate experience and knowledge of the investment operations and capital markets. The provider’s team should also be able to manage the entire data management process from start to the finish, to feed multiple downstream processes – from reconciliation and settlement, to accounting books and records, and compliance reporting.
The process starts with the service provider locating account data, and evaluating, establishing and maintaining your firm’s feeds and relationships based on your specific needs, with the ability to easily make adjustments should your needs change and you require additional data elements. The process continues with the service team taking care of daily data acquisition, formatting, content transformation and enrichment, complete with validation checks enabling staff to recognize format changes (whether announced or not) and proactively modify processes and alert your team.
Then the data is automatically validated to recognize these changes for completeness, while data and file types are verified, any missing data is captured, and any identified data issues are researched and corrected working directly with the source. All the while, the firm has complete transparency into the entire process.
With all the challenges investment managers need to manage and overcome, should firms be focusing their time and resources on data aggregation? Probably not. With a fully outsourced, proven data collection and aggregation service, they can save time, cost and risk while adding value to their entire post-trade process.
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Jennifer McMackin is the senior vice president and lead for Electra Data, an operations service that helps investment managers overcome the challenges of aggregating, validating and enriching data to drive multiple post-trade workflows. She also oversees Electra Managed Services, a scalable and cost-effective reconciliation service that helps firms simplify workflows, increase team productivity, and repurpose staff towards higher value.