Rethink data for next generation fund distribution

By Didier KAYL, Head, Business & Relationship Development, Client Service Management, Fundsquare

The fund industry is transitioning to a landscape in which real-time exchange and flows will be common and expected.

Supervisors have long been urging greater transparency, investor protection and financial inclusion, leading to heavier compliance and regulatory workloads for companies when distributing investment funds. 

Additionally, the way funds are distributed today is changing, thanks to technology advancements, digitalisation and new end-client behaviours and expectations.

The fund industry is therefore transitioning to a landscape in which real-time exchange and flows will be common and expected. Now, a fund transaction can take days, KYC formalities can be multiple for an investor, the fund creator has little idea of the final fund buyer. Tomorrow, data consumers in the distribution chain will take for granted on-demand access to real-time information.

Along with a digital transformation of the point of sales, these demands mean larger data volumes and flows at a time when data is becoming increasingly strategically important. If investment fund companies want to succeed in this new environment, then they need to become skilled at data and data exchange in such a way that enables them to unlock value.

Didier Kayl

Head, Business & Relationship Development, Client Service Management (Fundsquare)

Put simply, what is needed in the fund industry is a new and better way of thinking about data: how it is accessed, how it is delivered and how to create valuable data from the external use of its own data.

Holistic data management to drive business outcomes

To respond to these disparate requirements, the answer here is holistic data management specifically designed with investment fund information exchange in mind.

At its simplest level, this holistic data management is composed of two interconnected elements, data provision and feedback. As the feedback element suggests, these two are part of an ongoing iterative process between the data provider and the data consumer.

Iterative feedback allows the creation of additional valuable data that all those in the distribution chain can use to continually improve data quality and ensure that data is delivered efficiently and effectively. Beyond this, it enables actors to discover insights in the information and flows, thus allowing them to further enhance and improve data quality and delivery. Most importantly, it can then greatly assist fund companies in the chain to bring innovative solutions to the market based on the insights gained.

The underlying business goal of holistic data management is to be in position to continuously create value in the most efficient and cost-effective manner possible.

Improve information flows and interconnectivity at each step

Looking at such data management more closely, each of the two elements – provision and feedback – is made of three distinct components. For the data provision element these three are quality, accessibility and compliancy.

Data quality is the fundamental initial step in the holistic process. It is also the one where the fund industry needs to make the most work. Today’s complex, semi-manual and siloed approach to data, in which significant time and resources are devoted to finding and correcting inaccurate or incomplete information, needs to be replaced with a more advanced and company-wide approach that sees data quality as the basis of opportunity creation instead of a burden.

The second component in the delivery element is accessibility. In the fund industry, data is held in different formats across different repositories. Data providers, and by extension data consumers, need information across all these sources and getting access should be much easier and faster than it is currently. Compliancy is the third and final component of data provision. By this term, we mean ensuring that information gets to the right actor in the chain at the right time, whether they are an intermediary in the distribution chain, an end investor or a regulator.

Delivering quality data to the right actors efficiently is the first element in holistic data management. The second is enriched feedback, whose three components are observation, analysis and prediction. If the three components of data provision respond mainly to the needs of cost reduction and efficiency, the three feedback components enable data providers to approach a true digital service that will help create a digital ecosystem for fund distribution.

Holistic data management is the framework and to get the most benefit out of it and drive improved outcomes, new techniques, technology and tools will be utilised. These include big data analytics, machine learning and data lakes.

Data on demand for all actors in the distribution chain

Big data methods and analytics are at the core and will be used throughout the holistic data management process. Obviously, such techniques can be used to gain insights and make predictions but more fundamentally must be used for the initial data quality component to analyse the data on offer, then together with machine automation to cleanse and prepare data for all the following components.

A holistic data management foundation combined with the right tools and techniques will facilitate real-time, on-demand and automated access to information. Such access will ensue that communication and exchange are embedded throughout the distribution chain and fund companies can be more competitive and responsive.

The new way of data provision will affect all of today’s actors in the chain, the fund creators, the distributors, the fund administrators, the central security depositories, the transfer agents, the investors and so on. There is potential to bring benefits to all of these, particularly in the areas of efficiency and insight, thus enabling smarter, next generation products and services, as well as increasing transparency and growing the investor base.

AGEFI Luxembourg, November 2019

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