Almost as certain as death and taxes, accounting regulations impacting asset managers will remain in a state of perpetual motion. In Canada, for instance, the next phase of International Financial Reporting Standards (IFRS) implementation introduces what KPMG recently billed as an “unprecedented level of change” — affecting everything from how financial institutions classify and measure assets to how they account for hedging instruments. KPMG’s report also highlights that beyond changing regulations, the more demanding landscape is forcing organizations to rethink their philosophy around technology altogether. This translates into a pronounced shift as asset managers transition from legacy accounting systems to more standardized platforms offering the agility to keep up with today’s business needs.

In the past, firms had little choice but to build highly customized accounting systems. Though this allowed firms to tailor technology capabilities to the unique needs of the back office, it often required additional systems in parallel or applying other “fixes” to fill in the gaps. In turn, these workarounds increased both risk and technology costs related to the management of data and enterprise security.

Fast forward ten years, and not only has the number of financial products and asset classes grown considerably in size and sophistication, but so has the number of complementary applications tied into the accounting system. Indeed, an accounting system is rarely just an accounting system — it can be used for client reporting, analytics, or even as a makeshift data warehouse. These custom-built systems may produce the required outputs day-to-day, but they’re unsuited for change, whether it’s new regulations, investment strategies, or acquisitions. And the price of past customizations can be measured in units of time and complexity.

This technical debt, alone, is driving many asset managers to replace legacy systems. There will almost always be some level of customization, but by pivoting to a more standardized platform, managers are choosing to start with a clean slate. In turn, they can more easily absorb new innovations and capabilities, while simplifying the support model, which positions organizations to benefit from industry best practices.

Orchestrating the migration

While standardization certainly simplifies implementations, conversions still require thorough planning and flexibility. If the highest order goal is to instill agility into the back office, creating new workarounds cuts against this objective. This is why it is so important to focus on key principles when implementing a new system:

Define objectives explicitly…

Organizations must identify what it is that they want from the new system. This is why the proof of concept — and what we often see as a model office — is such a foundational component at the beginning stages of implementation. These exercises will align the system with the needs of the organization and allow teams to contextualize how the system supports an enhanced operating model.

…While staying flexible

Without understanding why, many organizations seek to replicate existing processes and workflows. A new platform presents an opportunity to rethink how new technologies can deliver operational efficiencies. This should be a consideration during the earliest stages and communicated to key constituencies to set expectations and gain buy-in ahead of the conversion.

Embrace agility

Deadlines and milestones are absolutely critical to keep the project progressing. However, organizations should not forget the ultimate objective is deliver the highest quality system possible. If a “go-live” date is scheduled for 18 months after a project begins, a lot can happen between the proof of concept and the conversion. Whatever new developments emerge, it saves time to stay flexible and factor any new considerations into the implementation.

It’s still all about the data

Data quality remains at the center of every successful conversion. This is why it is so important to create a comprehensive checklist that maps out all of the vendors providing data, how the data is used across the organization, and any potential gaps that may exist. Having the right data management solution with the appropriate policies and controls helps to support the governance model that has been implemented. Mock conversions can be staged to ensure the data appears as it should. And when the new system is set for parallel adoption, the reward will be a streamlined platform, free from any discrepancies necessitating quick fixes and workarounds.

The ongoing move from legacy systems to open, standardized platforms may seem foreign to asset managers who often cite their proprietary investment process or unique quantitative tools among their key differentiators. Yet, the competitive landscape has forced even the largest asset managers to reconsider where their core competencies reside.