The private credit market is experiencing an unprecedented wave of capital inflow, driving managers to scale up operations while facing mounting complexity. During our recent webinar Scaling Private Credit Operations: Overcoming Infrastructure Limits, Admin Dependencies, and Data Gaps, co-hosted with LPGP Connect, industry leaders Dan Ryan (Executive Director, Morgan Stanley Private Credit) and Piyush Singhi (Senior Managing Director, Credit and Private Funds, Indus Valley Partners) shared actionable insights on how to navigate infrastructure bottlenecks, admin dependencies, and data challenges across the lifecycle of private credit investments.
Based on their conversation, here are the steps managers can take right now to build resilient, scalable operations and future-proof private credit platforms for growth.
Laying the Foundation: Data Governance and Infrastructure Modernization
As private credit funds proliferate and portfolios grow, effective data governance has become non-negotiable for investment managers. It is critical to aggregate and maintain data integrity throughout the investment lifecycle. Modern firms need robust workflows and clearly defined ownership for each stage of data entry and amendment, ensuring information is logged and updated by the right people.
Key requirements for building a strong data governance foundation:
- Establish clear data ownership and roles for each stage of the investment lifecycle
- Implement workflow approvals before investment booking and funding
- Create systems that log all information changes with complete audit trails
- Enforce firm-wide data governance standards across all departments
- Define data fields and terminology to eliminate subjective interpretations
Establishing strong governance facilitates the timely, accurate dissemination of data that is key not just for investors, but for internal stakeholders and regulators who expect firm-level rigor. However, while standardized identifiers are the norm in public markets, private credit lacks this advantage. In addition, while liquid markets use identifiers and APIs to streamline portfolio monitoring, private credit relies on bespoke processes and custom-built systems. All of this means asset managers need to create their own standards for data tracking, reporting, and auditing, usually with specialized teams and fit-for-purpose technology solutions.
Quick read: Power of Golden Source of Truth in Private Credit
Integrating Systems: Navigating Fragmentation and Interoperability
Fragmented systems and vendor proliferation continue to be one of the biggest obstacles to scalable private credit operations. Often, operating models evolve into a patchwork of service providers, legacy tools, and new platforms that struggle to communicate effectively. There is significant tension between the need to keep technology infrastructure lean and the pain of onboarding new solutions. Implementation almost always takes longer than advertised, and data mappings between systems can vary, sometimes even for basic concepts like exposure.
To streamline integrations and avoid data silos, firms should:
- Conduct vendor capability assessments before onboarding new systems
- Map data flows across all platforms to identify inconsistencies and gaps
- Allocate sufficient time and resources for implementation (often 2-3x longer than vendor quotes)
- Establish clear accountability for data transmission between systems
- Standardize terminology across departments (e.g., exposure, valuation, risk metrics)
- Prioritize integration quality over the number of systems in use
Stakeholders should be involved early and cross-functionally, as differences in terminology and definitions across the organization can undermine even the best-designed systems. Standardizing data fields and enforcing strict data governance norms help ensure consistency and quality across departments.
The Fund Admin Reality Check
Third-party fund administrators (admins) were once touted as an operational panacea, but the reality is much more nuanced. While some asset managers report smooth operations, others struggle with delayed timelines and questionable output quality, especially as monthly or quarterly fund NAVs bump up against tight reporting deadlines. A key challenge is retaining top talent on the admin side, as frequent turnover can undermine service levels.
In our webinar, industry experts advocated for maintaining strong data governance, even in outsourced models, with centralized control over security masters, cash flows, and reconciliations. As firms expand, keeping admin models on a single-platform basis where possible is ideal, but growth often necessitates multi-admin structures. In these scenarios, deploying a shadow model becomes vital. This is an internal parallel process to double-check key numbers, reconcile discrepancies, and standardize reporting when data from different admins varies in quality or format.
To optimize your admin partnerships and mitigate dependencies, firms should:
- Maintain a single-platform admin model where possible as firms scale
- Implement shadow processes for multi-admin environments
- Reconcile data discrepancies between admins using standardized formats
- Establish clear SLAs for admin performance on intra-month reporting
- Invest in partnerships with data and technology-forward administrators
- Create incentives to retain top admin talent through consistent business and feedback
Market consolidation among admin providers continues, and those that leverage technology and data science to lighten the workload for managers will become leaders in the space as firms increasingly seek data-forward partnerships.
Scalable Operations: Building Processes for Growth, Not Headcount
One of the most significant risks for fast-growing private credit teams is “headcount creep.” Simply hiring more staff to cope with complexity is unsustainable. The webinar panel stressed it is imperative to build scalable processes with automated workflows for deal pipeline, closing, maintenance, accounting, and reporting. As asset classes and deal structures become more nuanced, systems must be adaptable and intelligent enough to support evolving requirements without major overhauls or manual workarounds.
To build truly scalable operations, firms should:
- Automate deal pipeline, closing, maintenance, accounting, and reporting workflows
- Build systems flexible enough to support evolving asset classes and deal structures
- Document processes and hire domain experts to support nuanced structures
- Replace underperforming systems promptly rather than building workarounds
- Engage service providers early when evaluating major operational changes
- Plan system migrations with clear project timelines and resource allocation
Equally important is forging strong partnerships with service providers. Peer networking allows managers to learn from comparable firms about which vendors truly deliver, while maintaining clear, contractual role definitions among counterparties helps ensure data integrity and seamless operations. When systems underperform or integrations break down, the willingness to replace underperforming platforms, even if difficult, is essential to long-term efficiency.
Automation and AI: Turning Data Into an Asset
With ever-increasing demands for real-time reporting and oversight, automation and AI are becoming indispensable. In fact, AI has started to deliver measurable value in private credit, especially in exception handling, reconciliations, and reporting. While much of this work is accomplished through vendor solutions, the future lies in developing targeted point solutions for specific use cases.
To implement AI and automation effectively, firms need to:
- Start with high-ROI AI use cases: asset setup, portfolio reviews, deal documentation
- Prioritize one operational problem at a time rather than broad agentic AI
- Leverage vendor AI capabilities before building custom solutions
- Ensure underlying data quality before deploying automation or AI
- Use AI for exception handling and reconciliation to reduce manual work
- Measure ROI and iterate continuously on point solutions
Still, the mantra “garbage in, garbage out” remains true. Success with AI and automation is directly tied to the underlying data quality and robust audit trails. Managers need to be realistic and focus on solving one operational problem at a time, leveraging networking to learn from industry peers and preparing to iterate continuously on both technology stacks and business processes.
Building for the Future: The IVP Perspective
As the webinar concluded, one thing became clear: private market firms can’t scale sustainably without reengineering the foundations of data and operations. Navigating the structural barriers in private credit requires a bold yet pragmatic approach. Here are few key takeaways:
- Invest in data governance as the foundation for all operations
- Standardize and integrate core systems to eliminate data silos
- Maintain oversight across outsourced functions through shadow processes
- Embrace automation for scale without increasing headcount
- Unlock data-driven insights and technology-forward partnerships with service providers
- Make tough calls around talent, processes, and platforms when needed
From data management and integration frameworks to reporting automation and workflow orchestration, IVP provides the infrastructure intelligence that allows managers to evolve from reactive operations to proactive, insight-driven organizations.
The future of private credit operations belongs to firms that treat data as an asset class of its own — one that demands the same rigor, governance, and precision as any investment.
