Digital transformation has been a focal point for information technology (IT) managers and business users alike for years. Often the low-hanging fruit around digital transformation is perceived to be operational enhancements that eliminate or reduce the time and cost of manual processes. In alternative investments, creating and distributing investor reports, uploading investor performance data and maintaining investor contacts are examples of repetitive processes. These activities tend to provide obvious starting points for integration with source systems, such as accounting and customer relations management (CRM) platforms.
I recently caught up with Ivar D’Silva from Resonaite, AI, whose firm has been instrumental in helping SS&C Intralinks clients achieve effective digital transformation through automation, and we discussed his impressions of where our clients have found the greatest value in digital transformation.
1. Digital transformation is about future-proofing. Few, if any, firms feel that hiring to scale as the size of the operation grows is a cost-effective strategy. In general, off-burdening staff from low value-add operations can keep hiring at the measured pace that ensures greater resistance to the ebbs and flows of business and lets staff focus on higher value operations that must involve a human being. Increasingly, those operations should fall in the realm of decision-making rather than data entry. Reviewing and approving a task initiated through automation before changes take effect such as approving documents to be distributed, and ensuring data, format and recipients look good is an optimization of a process that would otherwise have the team manually preparing the documents themselves.
Implied in intensely manual processes is the risk of inaccuracy due to human error. Every manual touch point increases the likelihood of data inaccuracy. Clean, accurate data is essential to driving effective business insights. Lack of confidence inspires even greater manual touchpoints in what may already be a resource-constrained investor services team.
2. Transparency and audit completeness is dramatically improved with the adoption of automation.. Rather than having limited insights into the upstream processes that caused
something to take shape, the interim steps taken in the preparation of data can themselves be tracked and logged. This makes incident investigation dramatically more effective by providing a single source of insight into all steps that factor to the incident.
3. Data integrity and data governance. Manual processes in one system may require access to other systems in which the data originates. A growing web of entitlements to disparate data sources creates a real data governance challenge. Each user with access to raw data represents a potential data leak. With automation to tie systems of record to systems of interaction, you can enforce granular role-based security that reduces the number of access points to source system data and minimizes data loss or leakage risk.
Among high-value investors whose capital general partners (GPs) are actively competing, those limited partners’ (LPs) operational due diligence processes increasingly place a heavy emphasis on the practices and procedures within the GP, including their security and data governance posture. Elimination of risky manual touch points in favor of well-governed automated processes drives confidence in the GP on the part of their most valuable LPs.
Conclusion
Private equity has historically lagged in data governance. But in a market where attracting capital continues to be highly competitive with longer fundraising cycles, it is even more important both from an operational perspective and from a competitive differentiating viewpoint to digitize operations to minimize burdens on staff, maximize data integrity and block data loss risks. To remain competitive, GPs need to choose technology partners whose platforms help them realize digital transformation through effective integration strategies.