The overall task of accounting, recording, storing and securing the millions of dollars' worth of transactional data flow that any given asset manager generates on a daily basis is complex enough.

But the challenge of ensuring that it is streamlined, error-free and available to be examined in real time by regulators is a defining trend for data management.

The impact of the SEC modernization ruling on data management, coupled with demands from other regulatory bodies around the world, cannot be understated, note researchers at Deloitte, in their latest analysis of mutual fund reporting.

"The breadth of information required by the new forms-combined with an increased number of filings and shorter timelines — will likely make it more challenging for asset managers to source and aggregate the necessary data components," the consulting firm states.

Todd Moyer, executive vice president of global business development at Confluence, one of several investment data management firms working in the industry, says that clients have already had to overhaul how they process their data as a result.

"To meet those regulatory obligations firms have had to put more effort than ever into sourcing, loading, aggregating, scrubbing and reconciling the data, and calculating responses before filing with regulators," Moyer says.

Moyer is among several leaders contributing their perspectives to Money Management Executive on the leading trends shaping industry processes and investment into data management.

The universal advice to any asset management firm is to be investing in their data management infrastructure to be better equipped to deal with increasingly complex demands, not only from regulatsors, but also from clients who expect greater product transparency.


The biggest data management issue our clients are dealing with is around how to streamline the collection, validation and distribution of the growing volumes of data that regulatory bodies globally are asking for — from AIFMD and Form PF reporting for alternative funds to Form CPO-PQR reporting for commodity pool investments to, perhaps one of the onerous of all, Form N-PORT filings for '40 Act mutual funds required under the SEC Modernization ruling.

To meet those regulatory obligations firms have had to put more effort than ever into sourcing, loading, aggregating, scrubbing and reconciling the data, and calculating responses before filing with regulators - oftentimes processing and validating the same data multiple times for different filing obligations.

The challenge firms are facing is how to build a data management model that delivers efficiencies across the enterprise.

ather than siloing duplicate sets of regulatory data across the various business lines, they're looking to build a single source the entire enterprise can use and reuse. That model delivers obvious efficiencies and reduces potential for reporting errors.

For the past eight years, the industry has created one-off solutions to tactically deal with each regulatory reporting issue as it came along.

As the industry shifts from getting through the day to growing their business, they're finding they need to convert those tactical responses to a unified strategic solution, a phenomenon known as regtech — a subset of fintech that facilitates the delivery of regulatory requirements faster and more cost-effectively than existing capabilities.

The industry is now a journey toward digitalization, ultimately providing a more efficient, agile operation, flexibility on the use of output and greater transparency to investors and regulators. They're beginning to make significant progress toward achieving their automation goal, and are now fully embracing a technology-driven data management model — viewing it as an asset that touches far more than just regulatory compliance.


The need for analytical wholesaleing is greater now than ever. Asset managers are under cost pressures and operate in a highly competitive environment while advisers desire fewer, high quality interactions with wholesalers.

Analytical wholesaling requires timely insights delivered through simple to use technology. But, many asset managers are plagued by data overload and disconnected systems which inhibit quality insights. Firms are often challenged to turn mountains of sales results, marketing and sales activity, research, social media and website traffic into actionable information.

To be successful, asset managers need broad data coverage or risk deriving false conclusions. Sales data should include activity for funds and ETFs across channels including RIA, independent and registered IBDs, wirehouse, and online channels, for retail and institutional customers.

Asset managers must organize their data and employ advanced analytics and machine learning to deliver the right message to the right advisers at the right time and benchmark results from sales and marketing activities to improve outcomes.

To be effective, analytical wholesalers must have access to timely insights derived from data and information that is refreshed regularly to find trends and spot opportunities. Knowing what channels are driving sales, what products are gaining assets, what marketing initiatives resonate with intermediaries and shareholders, and how competitors are performing are essential to survival and growth. Firms that harness the power of data and analytics will outpace those who rely on traditional cold-calling, mass mailing, and conference attendance.


Big data is a hot topic in asset management — investment managers are hiring data scientists and implementing advanced data management tools in the relentless pursuit of returns. A Boston Consulting Group whitepaper from 2016 notes that "competence in advanced data and analytics will define competitive advantage in the industry."

Relatively little attention is paid to the value of advanced data analysis to fund operations. Yet changes brought by data management to back- and middle-office functions could have significant bottom-line impact for asset managers.

Just as the front office focuses on identifying idiosyncratic and systemic risks in investment portfolios, so should operations be concerned with finding outsized and ongoing cost drivers.

Today's investment practices generate a massive and growing universe of data, including the metadata that is crucial to the forensic work of diagnosing and handling exceptions in operations. This universe can quickly expand beyond the time and patience of operations teams to perform deeper analysis, making it that much more difficult to identify systemic issues in the face of more and more types of data.

The same big data practices and tools that are coming to market for the front office can provide an opportunity for the back and middle offices to increase the leverage in operational analysis and create an active data asset.

A data strategy can help identify patterns that improve the manager's understanding of the true cost drivers, and more importantly, where internal investments should be made. With volumes and breadth metadata on the rise, it is a ripe area for future investment.


When asset managers fail to deliver a first-class digital experience or leverage their clients' data to tailor advice, it erodes satisfaction in the asset manager.

In addition, asset managers themselves are being handicapped by tired technology tools. Making good portfolio decisions typically requires consulting multiple different systems -Investment Book of Record, trading, market news, pricing, etcetera. As a result they are less efficient and less effective in serving investors, which compounds the client satisfaction issue and makes operations costly.

We are addressing how to make the investor digital experience intuitive, involved and individual. That means the asset manager curates news, social media and other content that is relevant to each demographic being served, such that when investors access their client portal for portfolio information, they are also getting topical information without leaving the portal.

We think the biggest data trend in asset management is automated matching of content to portfolio details. For example, if an investor holds Apple stock, the investor will get automated Apple news, pricing and other relevant content integrated with the relevant holding, tax lot and performance information.

Likewise these tools can be used for the asset manager's advisor and money management portal, such that content that supports portfolio decision-making is pre-integrated with other portfolio manager tools.

This trend is at the very early stages of being exploited, but promises to massively increase client satisfaction and to drop asset management operational costs.


Asset managers are turning to data and analytics to understand the market and better position their funds.

The data available today is much more detailed and powerful than what was previously available, providing information on how managers stack up to peers, which products are attracting investor attention, or which world events are impacting what investors and consultants care about.

With access to detailed data on the marketplace and competitive landscape, asset managers can gain understanding of investor and consultant needs; understand how their products are being perceived by consultants and investors; identity relevant opportunities for prospecting; better position products in the market and against competitors for success; and make better decisions about new product development and launches.

Subscribe Now

Access to premium content including in-depth coverage of mutual funds, hedge funds, 401(K)s, 529 plans, and more.

3-Week Free Trial

Insight and analysis into the management, marketing, operations and technology of the asset management industry.