Ignites recently reported that the number of fund companies reporting net asset value errors increased by 29% in 2022 compared to 2021, with 129 of those funds requiring NAV restatements. Turnover and complexity were primarily pointed to as the causes, compounded by higher market volatility yielding errors more material than in times of lower volatility.But the lurking problem behind what the article raises is repeated failures of the NAV control environment.
Data quality and data capabilities within an asset management organization are vital when addressing operational transformation. Often, data practices are an afterthought when attempting to engage in an operational transformation initiative. The reality is that organizations lacking good, clean data and solid data practices will find implementing the future state model challenging, longer than necessary, and more costly to deploy.
Olmstead recently conducted a study on the state of Distribution Intelligence (DI) across asset managers. A key takeaway: while DI has established itself as a mainstream function, ROI is largely anecdotal, and the best-in-class only recently, after significant investments (in data, tools, and talent), have positioned themselves to increase sales adoption andimpact.
An interesting trend we have seen is the growing appetite for transformation services from smaller asset managers. In the past, the mid to large to mega asset managers were the primary users of our consulting services. While that demand persists, we see the asset managers on the lower end of the AUM spectrum increasingly revisiting their operating models, modernizing their data platforms, and upgrading their digital capabilities on the manufacturing and distribution sides of the house.
The ever-changing landscape of the financial markets continues to influence how investment managers evolve to keep pace. Increasingly, firms are shifting from a bottom-up, siloed approach to a top-down, orchestrated effort to holistically transform the investment lifecycle, “front-to-back.”
Given the magnitude of change and the critical importance to the firm’s success, these large-scale transformations will no doubt feel daunting. You may ask yourself, where should I begin? At the front of the investment cycle? The middle and back? Or at the foundation, the data strategy? As the adage goes, “Which came first, the chicken or the egg?”
To better contemplate this question, let us take a closer look at each option.
Asset managers spent decades implementing portfolio accounting systems, making them the center of their systems architecture by integrating numerous other applications into it. We call this an app-centric architecture. Fast forward, the industry has been unwinding this and moving towards a data-centric architecture. Why the shift? To engineer in essential business agility required to respond to opportunities and threats, allowing for timely insights, innovation, and transformation. Such nimbleness simply wasn’t possible with the monolithic accounting platform as the beating heart in the middle and data trapped in various pockets throughout the architecture.
What does it mean to be information-centric? We’ve explored the definition and uses of your information under management(IUM), and talked about information management ideals, but now let’s explore if your firm is truly information-centric.
We’ve defined Distribution IUM and explored why you should seek to manage the internal and third-party data. The next step is to look at where all that information is stored. Firms have found errant data in their CRM, expense solutions, website, marketing, sales, and email systems. Some firms find them in Excel! While the data may live in various sources or applications, there is one key question that needs to be answered:
This blog is the first in a series where we explore how your firm can make the transformation to a data-centric firm.
An operating model that once worked brilliantly ten or even five years ago may no longer be producing the best results for your organization today. As the asset management environment changes over time -- more complexity in asset and transaction types, cost pressures, regulatory changes -- the op model must continue to evolve. Moreover, the pandemic underscored that change doesn’t always come with an advance warning. The status quo can shift in an instant, and last year served as a test of the vitality of firms’ op models, exposing and exacerbating preexisting weaknesses.
It may seem that it’s never the right time for a review; firms today are knee-deep in the daily grind. But now that the pandemic’s dust has finally begun settling, it’s time to dig out in order to spend some time today to benefit tomorrow…and prepare for whatever may be next. So here we’re exploring 4 key triggers to initiate an operating model review.