Paperless Technology Solution
Gurd shola Addis Ababa,
Ph: +251936515136
Work Inquiries
Ph: +251936515136

Digital transformation could solve data fragmentation in the private markets – VentureBeat

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Watch here.

Private markets have an outsized impact on global capitalism. They move trillions every year to funds and investments, often steering them into high-tech development ventures. Yet, the funds themselves are underinvested in technology, investing just a third to half of what public-facing financial institutions commit to innovation as a percentage of their revenue. The resulting hangover of legacy methods has hampered the investor experience and data management from the inception of most funds. This bottleneck – at the very point where capital flows in – has confounded both investors and fund managers and persisted through the funds’ lifecycle. 
Private markets, an engine of investment in tech innovation, have been overdue for digital transformation of their critical activities related to raising capital and fund management. Deal execution and compliance also depend on those processes. Virtually every participant — from investors (limited partners, or LPs) to fund managers (general partners, or GPs) and their lawyers and fund administrators — has felt the inefficiency of archaic paperwork when onboarding investors. Relying on PDF forms, Excel spreadsheets, and manual processes has turned more problematic recently, thanks to a talent shortage that coincides with the need to scale for a wider LP market that includes retail investors.
Post-COVID-19, more funds have accelerated their adoption of workflow automation and this is a major step ahead, but not the entire solution. That’s because a major obstacle to optimizing fund formation and relationships with LPs is in the longstanding sediment layers of discoordinated data on which the industry runs. Investors, regulatory authorities, each fund or fund family, and different portfolio companies all structure and see their data differently. 
Meeting that challenge is a complex exercise in strategic architecture choices and data “translation.”
Process automation can radically improve the experience of investors, reduce their data entry errors, meet compliance requirements, and manage the LP life cycle. Workflow to collect required information replaces onerous, friction-marred sequences to qualify and onboard investors. In addition, it guides investors through entering their information correctly and performs data integrity checks. Funds can cut onboarding time and friction, speed up fund formation, and provide the red carpet experience their investors expect. Now, when private equity investments have slowed, this is compelling for fund managers. 
As it does in many industries, an automated platform can capture and validate data once, hand it off automatically and avoid transcription errors. This reduces processing costs, but also improves the data quality and throughput further downstream.
Once fund operations are up and running, it’s apparent that each fund has its own data model, and portfolio companies have their own structures for reporting results. An industry-wide standardized data protocol would be the ideal solution for private markets, but it’s also elusive and will require agreement across numerous actors. That means it’s up to practitioners and software vendors to adopt tools and methods to normalize data and work around the fragmented, disparate data structures. Building this kind of platform calls for careful architecture tradeoffs between being prescriptive (“our way, or no way”) versus more adaptive (“your way, when necessary”).
A workflow solution needs to balance a standardized, set approach against the ability to customize and match specific funds’ practices. Larger funds, in particular, tend to require more customization. Keep in mind that a solution will need to flex to match changing compliance requirements; it’s imperative to verify that every investor is qualified and meets SEC requirements and keep the fund in compliance with its fiduciary obligations to investors.
No fund manager wants to be left behind as expectations rise, and workflow platforms provide a common starting point, particularly if they embed domain-specific business logic. Cutting-edge technologies are likely to be integrated into private markets as they embrace digital transformation.
By taking the first step in digital transformation – workflow automation – private market funds are fundamentally improving how they operate, taking friction and lost time out of the investing process. At the same time, data quality and confidence in compliance have improved, along with investor satisfaction. Going forward, adaptable architecture and multilayer data translation using new technologies can continue the gains that private market funds have achieved in the first phase of innovation.
Alin Bui is the cofounder and Chief Strategy Officer at Anduin.
Welcome to the VentureBeat community!
DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own!
Read More From DataDecisionMakers
Did you miss a session from Transform 2022? Head over to the on-demand library for all of our featured sessions.
Did you miss a session from Transform 2022? Head over to the on-demand library for all of our featured sessions.
© 2022 VentureBeat. All rights reserved.
We may collect cookies and other personal information from your interaction with our website. For more information on the categories of personal information we collect and the purposes we use them for, please view our Notice at Collection.


Post a comment

Your email address will not be published. Required fields are marked *

We use cookies to give you the best experience.