Making the case for fund data ops, one project at a time
When funds need to solve one specific data problem, they’re creating an opportunity to discover how data operations can deliver broader efficiencies and savings.
A fund administrator was having data problems in its securities business. They reached out to data management consultancy Reformis, which worked with a forward-thinking group within the organization to show how powerful data operations can be when done right.
Adam Davis of Reformis highlighted this partnership on a recent Harmonate webcast as an example of how targeted projects can win buy-in for broader data operations initiatives that can enhance efficiency and benefit the bottom line.
When Reformis was brought in to help resolve the securities issue, the team launched a discovery phase. They spoke to different people within the business to understand the issues that they’re facing.
As is often the case, a group emerged who looked at data issues through a wider lens. They knew what specific issues existed in the company, recognized the wider challenges around data management and wanted to build momentum toward broader change.
Reformis worked with these individuals to solve the specific issue at hand — and did it very well — and then showcased that success to the rest of the business.
The project’s technical phase began with a relatively light touch. Reformis used a combination of in-house tools and slight process changes to streamline and centralize the fund’s data security. These changes allowed the client to automate the ingestion of different system and vendor files, raise relevant exceptions and automatically match and create master data sets.
When these relevant exceptions raised their heads, machine learning software observed humans fixing the issues and added those lessons to its arsenal of automation. Over time, this process of exception-based machine learning becomes 80 percent more efficient than humans working alone.
Although these changes did not drastically change the roles or workflow of the teams working within the securities business, they revamped the client’s process for data security, creation and mastering, creating a range of efficiencies and cost savings over time.
The client’s data redundancy issues were significantly reduced. They were no longer requesting data from the same vendor twice or requesting the same sets of data from multiple vendors, a direct benefit in terms of cost to the organization.
Automating the exception-management process greatly reduced the time users spend checking data and helped kickstart a more proactive approach to data management as opposed to the reactive approach still seen at many funds.
Lastly, these tools were part of a one-stop, intuitive digital interface, making these new tools accessible to everyone who needs them rather than keeping them siloed within the IT or compliance departments. All things related to securities were now in one place and configurable to the needs of those using it.
Emerging from a pandemic that has forced digital acceleration across industries, Wall Street is also turning its attention to the industry’s data-driven future and talking about what digital operations for funds and automation really look like.
Every organization will adopt a different approach to data operations, but getting started on the path to enterprise-wide integration — or rerouting your journey to get there — can be challenging.
Pro tip: keep an eye out for targeted projects that can prove hunches that data operations benefit the business and create a model for ongoing innovation.
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