In the wake of the tumultuous post-COVID years, it’s not surprising that many asset managers are eager to migrate to a service provider’s robust operating model and reduce the risks and overhead of maintaining their existing operations. As a result, there has been a significant increase in outsourcing deals initiated from the corner office, with decisions being reached before thorough due diligence has been completed. However, when it comes to due diligence for middle office outsourcing, there really is no “fast pass.”
While middle office transformation remains a priority for asset managers, many are realizing that there is a directcorrelation between success and their data capabilities. Consequently, more firms are prioritizing data at the start of their transformation journey – but not all are realizing the intended benefits.
Performing robust due diligence when searching for an outsourcing partner may someday go from a best practice to a regulatory requirement. This past November, the SEC proposed an outsourcing due diligence rule that would expand 17 CFR Parts 275 and 279 to regulate outsourcing initiatives carried out by investment advisers.
The markets have been tumultuous these last few years, and this whirlwind of volatility has hastened the need for change, driving the upcoming move to T+1 settlement. Equities, corporate debt, and unit investment trusts in the U.S. will move to a T+1 cycle on May 28, 2024. Canada is following suit; they intend to align the timing of a move to T+1 with the United States. No other global markets plan to make the change at this time, although some are considering it for the future.
An effective client segmentation strategy will enable sales and marketing teams to provide the most valuable clients with an optimal client experience while improving sales results and lowering costs. While many firms have invested heavily in developing segmentation models, much of the industry still relies on individual efforts to rank clients. This happens on a small scale using only one or two data points, such as sales or assets. Firms have an opportunity to standardize segmentation methods by building a model that pulls information from the volume of internal and external data available today; without making their sales professionals become data analysts. The results will provide territory management guidance, break down silos between sales and marketing, and ensure strategic enterprise goals are met. This opportunity allows firms to simultaneously build a repeatable process that can work at scale for your business and adapt to changes to channel mixes or product focuses.
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.