Transforming fund operations and why data migrations matter
Fund operations have shifted. Legacy platforms are being retired as technology evolves, clients expect faster onboarding and regulators want cleaner, auditable data. These pressures have made data migrations more frequent and more visible.
When data migrations work, the numbers balance, investor records carry over cleanly, and reporting continues without surprises. When they don’t, reporting breaks down in full view of clients. Whenever a firm transitions to a new system, takes on a new client, or consolidates years of data from multiple platforms, strategic migration becomes critical to success. Asset managers and fund administrators should view these projects as central to operations, not just technical undertakings.
A well-executed migration leads to cleaner data, faster reporting, and a scalable system for growth. As detailed in our insights on digital transformation in fund administration, whether replacing a legacy platform, onboarding a new client, or consolidating systems after an acquisition, these projects are where operational resilience meets strategic growth. By approaching data migration as a strategic priority, firms can unlock new efficiencies, enhance transparency, and future-proof their operations in a dynamic marketplace.
High stakes: complexity, risk, and reward
Migrations are rarely simple. They often pull from old systems and multiple data sources. Usually, they involve complex fund structures, and tight regulatory deadlines put a clock on completing the work. Every team feels the pressure: operations wants clean reconciliations; IT needs stable integrations; compliance checks every rule; investor relations needs reporting. Without strong governance, projects can quickly go off the rails.
The manual nature of most processes - including spreadsheets flying back and forth and macros being patched together -means initiatives often stall. Technical challenges range from multiple data formats, legacy fund structures, and integration with new platforms, especially when integrating data from a new client’s systems. Organisational hurdles, such as coordinating stakeholders and maintaining reporting continuity, add further layers of risk.
These gaps create real risks, including missed reporting deadlines, inaccurate Net Asset Values (NAV), and reputational damage. Successful migrations depend on both technology and method: clear ownership, early communication and teams who know the fund environment inside out.
From strategy through execution
A sound migration strategy begins with understanding business objectives, legacy system challenges, and client onboarding requirements. Next comes detailed data mapping and clear stakeholder alignment.
Execution leverages AI-enabled tools to automate labour-intensive tasks, reduce errors, and accelerate timelines. Change management is integral to ensure teams are engaged, processes are optimised, and risks are proactively managed. The core competencies required are include below.
Agility
Begin by establishing early standards, clear ownership, and flexibility to adjust as data quality becomes clear. First-cut mapping files and simple controls help sustain project stability throughout changes.
Experience
Deep fund accounting and private equity knowledge help interpret legacy data, test allocations, reconcile positions, and design the reports needed for cutover. This domain expertise minimises rework and grounds decisions in fund operations.
Innovation
Apply automation and AI tools to repeat tasks such as data extraction, transformation and reconciliation. This reduces manual effort, shortens testing cycles and frees teams to focus on checks that require judgement.
Migrations that worked
A private equity fund needed to migrate fund accounting data from multiple legacy administrators into Investran. The data was fragmented, partner allocations were inconsistent and timelines were tight. We worked with them to develop an approach that included:
- Established governance and detailed planning from day one.
- Built allocation testing files, reconciliation templates, and a GL database to standardise recurring work.
- Leveraged automation tools: Alteryx and PowerQuery reduced manual intervention.
- Backfilled operational roles so client SMEs could focus on migration-critical tasks.
The outcomes were timely, accurate deliverables, and a strengthened client relationship. The migration finished ahead of schedule, setting the stage for future automation. Key steps included:
- A bespoke target operating model aligned with strategic objectives.
- Parallel testing to validate data integrity before cutover.
- A new reporting library for investor and regulatory outputs.
The result was a smooth transition with no missed reporting deadlines. The client now benefits from faster reporting cycles and a scalable operating model. We also recently worked with a global asset manager that won a major mandate and needed to onboard the client’s data while maintaining BAU operations. The project succeeded based on:
- A phased migration plan to minimise disruption. Implemented automation workflows using Alteryx and PowerQuery.
- Change management and training programmes to ensure adoption.
- Backfilled operational roles to keep investor servicing uninterrupted.
The Outcome was seamless onboarding, accurate NAVs, and high user confidence in the new processes. Another successful migration involved an asset manager that needed to retire an outdated fund accounting system and implement a modern platform to support growth and compliance.
AI as a practical accelerator
In a recent article on AI Plays for Smarter, Profitable Fund Administration, we outlined the role of advanced analytics, automation, and intelligent data management. These can streamline processes, enhance accuracy, and enable teams to focus on higher-value activities, ultimately driving operational efficiency and profitability across fund administration. AI tools can:
- Enhance data cleansing and normalisation at scale, including onboarding new client data, by streamlining workflows and automating repetitive tasks.
- Simplify mapping and reconciliation across complex datasets, making onboarding new clients smoother through intelligent recommendations and automated processes.
- Identify anomalies and exceptions early, providing additional assurance during critical phases, such as client onboarding, through proactive monitoring and alerts.
This approach leads to faster project delivery, greater accuracy, and reduced dependency on manual spreadsheets, freeing teams to concentrate on strategic priorities and ensuring a successful onboarding experience for new clients.
Data migrations are inevitable. The question is whether they become a painful distraction or a catalyst for transformation.
