Migration has become a strategic bottleneck for asset servicers: every platform modernization, fund onboarding or transfer agent (TA) transition depends on moving complex data safely, yet migration budgets and timelines keep shrinking. The economics of traditional migrations, with their long lead times, high one‑off costs and limited reuse, no longer work in a world of recurring consolidation and regulatory scrutiny. This insight article explains how financial market infrastructures can transform migration economics by combining industrialized methods, reusable migration platforms and, where appropriate, low‑code and AI accelerators to achieve 30–40% faster delivery with lower run‑rate cost and stronger, auditable controls.
The migration pressure point
Asset servicers face a fundamental paradox: migration has become urgent, yet execution remains constrained by legacy complexity.
The ongoing consolidation of asset managers and asset servicers is increasing the pressure on service providers to onboard existing fund structures within short timeframes and at minimal cost. Since migrations are perceived as additional expenses that stakeholders are reluctant to fund, asset servicers are often required to integrate existing structures quickly. Prolonged onboarding timelines can significantly erode their margins, particularly when no dedicated budget has been allocated for such activities.
This is equally true for fund launches, platform replacements and transfer agent (TA) migrations, where investor and AML/KYC data must move without disrupting day-to-day operations.
The result: as migration timelines have compressed from 18-24 months to 6-12 months, frictions between speed requirements and quality standards have exploded. Organizations are increasingly realizing that they need repeatable, factory-like migration capabilities, not one-off projects, if they want to sustain this pace.
The unique complexity of asset servicing migrations
Unlike typical technology modernizations, asset servicing migrations face distinctive constraints:
It has become increasingly clear that traditional waterfall project methodologies, with their heavy documentation and extensive manual testing, cannot resolve these tensions. A new approach is needed.
Modern migration tooling:
The game changer
The convergence of modern migration tooling addresses multiple pressure points simultaneously. This toolkit typically combines:
When they are available, LC/NC platforms compress timelines by enabling business analysts to directly implement transformation logic through visual interfaces. In other contexts, teams can achieve similar benefits using configuration‑driven rules engines, parameter files or structured templates on top of traditional ETL and scripting. In both cases, fund accountants, transfer agent teams and operations specialists can specify business rules without heavy translation layers, reducing communication overheads and accelerating validation cycles.
Generative AI introduces intelligence into traditionally manual activities. One of the most significant impacts, when organizations choose to adopt it, is intelligent mapping suggestions. For migrations involving 500+ data fields, GenAI proposes 60-70% of mappings with high confidence, reducing mapping phase duration by 40-50%. Where GenAI is not yet in use, similar efficiencies can be achieved over time by building reusable mapping libraries and pattern catalogs across successive migrations.
In practice, much of this efficiency comes from starting with pre‑configured data models and mapping templates for leading asset servicing platforms, such as Multifonds, Investran, eFront, Allvue, Fernergo and other industry solutions, and then tailoring them to each client’s specific structures and controls.
Additional GenAI capabilities include:
- Automated test case generation based on existing data and process patterns.
- Data lineage documentation that shows how each key data element moves and transforms across the migration pipeline.
- Real-time technical documentation and change logs that reduce the typical documentation drift seen in lengthy or multi-wave programs.
When embedded in a governed migration platform and combined with LC/NC tools, these capabilities enable asset servicers to industrialize migrations, apply consistent controls across batches of funds or investors, and reuse patterns for subsequent transformations.
Quantified impact on migration economics
Organizations that combine industrialized migration methods with modern tooling achieve:
Once a reusable migration platform and pattern library is in place, each additional fund range, business line or TA migration benefits from existing mappings, rules and test assets. In our experience, anchoring this platform on reference data models for widely used industry solutions further accelerates delivery, as many core entities and relationships are already understood and codified.
Implementation realities
Success requires careful implementation aligned with operational realities:
Embedded governance: All AI-assisted suggestions require validation by domain experts before implementation. We recommend that initial phases use limited AI assistance with extensive validation, before levels of automation are increased as teams develop confidence.
Operating model evolution: Traditional organizational structures with distinct analyst, developer and testing roles often prove suboptimal. Forward-thinking firms are experimenting with integrated delivery pods combining domain expertise (fund accounting, TA, AML/KYC), data engineering and testing within autonomous teams. These pods are then aligned to migration waves or batches (e.g. clusters of funds or investor populations), enabling consistent quality and faster learning.
Phased approach: Pilot programs focused on specific fund types, asset classes or investor segments allow capability development while managing risk. These pilots are followed by scaled implementation and operational integration in controlled batches, where each batch passes through a standard set of steps: data acquisition and cleansing, mapping and transformation, validation and load, reconciliations and business review. This structure provides sponsors with clear quality gates and acceptance points, often aligned to groups of funds or defined investor lots. Importantly, these principles are technology‑agnostic. Many asset servicers prefer to implement them using existing enterprise standards such as established ETL tools, SQL/Python‑based transformation scripts, and enterprise scheduling and monitoring platforms. LC/NC and GenAI are powerful accelerators where they fit governance and risk appetite, but the underlying approach of configuration‑driven rules, automation, robust testing and clear governance can be implemented on a wide range of technology stacks.
Practical implications
Financial market infrastructures that develop strategic capabilities in LC/NC platforms and GenAI applications, while maintaining appropriate governance, will establish competitive advantages that translate directly into:
- Improved client and investor experience during migrations and onboarding.
- Reduced operational risk and fewer unexpected post-migration issues.
- Enhanced ability to capture growth opportunities from M&A, new product launches and platform modernization.
Three factors create urgency:
- Technology maturity has reached production-readiness for regulated financial services use cases.
- Early movers are establishing difficult-to-overcome capability advantages, including reusable migration platforms, domain-specific rule libraries and trained delivery pods.
- Migration demand continues to accelerate as asset servicers replace legacy platforms, consolidate books of business and support complex TA and fund administration transformations.
Organizations that delay risk falling behind competitors already realizing 40% timeline improvements and material cost reductions on complex, multi-jurisdictional migrations. The question is no longer whether to explore these technologies, but how quickly to build an industrialized, governed migration capability that can be applied across multiple use cases and client portfolios.
Not every organization will run dozens of migrations per year or require a fully permanent “factory” capability. However, even for a single large platform replacement or TA transition, applying these industrialized methods and leveraging pre‑configured data models significantly reduces risk and cost. Where there is ongoing demand, the same factory setup can then be reused and extended across additional migrations; where demand is one‑off, it can be operated as a time‑bound migration cell for the duration of the program and then decommissioned or scaled down.
How we can assist you section
KPMG has made a significant and intentional investment in people and technology to de-risk the complexity of business‑centric data migrations in asset servicing, custody, fund administration and transfer agency. Our approach is technology‑agnostic but automation‑first: we work within your existing technology standards (ETL, scripting, APIs, data platforms, LC/NC where available) to build a governed, reusable migration capability, often accelerated through pre‑configured data models and mappings for leading industry platforms such as Multifonds, Investran, eFront and comparable fund and investor solutions.
We call it KPMG Powered Data Migration – our holistic approach to data migration that takes a business outcomes focus to enable a smooth cutover, minimize business and customer impact, and build stakeholder confidence through transparent, auditable delivery.
Powered by automation and AI where appropriate, we address every aspect of business‑critical migrations, from strategy through to execution, under a variety of delivery models tailored to your context. Our people, technology and methods are proven to deliver in a controlled, trusted manner, enabled by our scalable, modular migration platform and method, whether this is implemented on top of existing ETL tooling, data platforms or low‑code components.
Key characteristics of our approach include:
- A reusable migration platform that supports multiple migration waves or batches, rather than a one-off script for a single project.
- Integrated domain and technical teams (fund accounting, TA, AML/KYC, data engineering, QA) working in pods aligned to your migration batches.
- Strong emphasis on data quality, reconciliations and evidence, giving senior management, clients and regulators assurance that migrations are safe and controlled.
Depending on your strategy and internal capacity, we can either design and hand over this migration factory to your internal teams, or operate it for you as a managed service for the duration of the migration program. In the latter case, KPMG runs the day‑to‑day factory operations (batches, loads, reconciliations, reporting) under your governance, allowing your teams to focus on key business decisions and oversight.
Our successful migrations range from relatively small customer/platform migrations to global multi-jurisdictional, multi-phase migrations under a “factory” delivery model. These include complex asset servicing, TA and fund administration transformations for leading institutions, where investor and AML/KYC data must be migrated without disrupting daily operations.
What does this mean for you? We partner with you to bring all of our experience to de-risk the delivery of migrations, increase efficiency and trust, and empower you to move forward with confidence – whether you are facing a single, complex platform or fund/client migration or looking to build a repeatable migration capability you can leverage for future changes and consolidations. In both cases, we can operate the migration factory alongside your teams or transition it fully into your organization once the program is complete.
