Funds Europe talks to SGSS’s Sarj Panesar about the importance of distribution data.
Much has been made of the role of data in today’s economy. It has been dubbed the new oil, black gold and the latest great commodity. However it has also been pointed out that data is meaningless unless it can be used to create a valuable outcome.
In the world of fund distribution, data can actually be used to great effect, according to Sarj Panesar, Head of Business Development, Asset Managers, at Societe Generale Securities Services (SGSS).
There has always been a need for asset managers to understand their clients but the technology has not always been there to extract and analyse distribution data and apply it to client behaviour. Now that it is, fund administrators are looking to capitalise.
SGSS has launched D-View, a digital data tool to support asset managers’ distribution plans. There are three main selling points for the service, says Panesar – the insight into clients’ buying and selling behaviour; a benchmark on the success of their product launches; and compliance with new rules and regulatory requirements.
The demands within MiFID II around product governance and ‘know your distributor and client’ rules have been a major change for the asset management industry and a major driver of the increased interest in distribution data-related services.
Helping clients navigate the choppy waters of regulatory requirements across Europe is not entirely new ground for fund distributors and despite the efforts of the EU authorities to create a more harmonised marketplace, via Ucits, the AIFMD and MiFID, some key differences remain when it comes to distributing funds in different domiciles.
MiFID II has taken the regulatory requirements to a whole new level in terms of the demands around transaction data. Plus asset managers have begun expanding their distribution ambitions in recent years, venturing into emerging and frontier markets, and relying on asset servicers for advice.
But the biggest selling point for D-View is the technology behind it, says Panesar. More specifically it uses data lake technology – which stores and aggregates large pools of data from transfer agents across multiple domiciles. “The data can be easily integrated and does not have to be reformatted. It makes it a far cleaner process when interrogating the data,” says Panesar.
The platform is built on open architecture to allow it pull in data from other external parties – transfer agents (TAs) and distribution platforms. Such a capability is a pre-requisite for any service aimed at any asset manager that has both domestic and cross-border fund ranges and works with multiple TAs and platforms. “They all need a comprehensive and holistic view across their client base,” says Panesar.
The D-View platform also has a customisable dashboard feature designed to give clients a consolidated view of their fund distribution data across domiciles along with flexible tools that allows them to drag and drop data and change the views as required.
While the concept of dashboards is an increasingly popular one in the operations world, it is the content that is different, says Panesar. This content includes fund inflows and outflows detailed by country, investor type, fund type, ISIN code and compared to assets under management; top 10 distributors ranking for each fund; and access to five-year data history.
“We have had a lot of interest from the chief financial officers,” he says. “They are the ones arranging the retrocessions and paying the bonuses. But we have also seen greater interest from the heads of distribution that want to see their funds are being sold, the heads of marketing who want to gauge the success of their product launches, and the heads of product that want a clearer view of who is buying their funds.”
The philosophy behind D-View is to get the best possible value from the data available, says Panesar. “We have been talking about this for more than 15 years but it is only in the last few years that the technology has made it possible.”
The platform is still in what Panesar describes as its ‘alpha one’ phase but there are plans to increase the breadth of data available. It currently includes data from funds domiciled in Luxembourg, Ireland and Germany and, from 2019 onwards, will add funds from France, Italy, UK and Switzerland.
There are also plans to incorporate greater use of artificial intelligence (AI) in the next phase. The use of AI overlays can help managers to model various scenarios against their distribution data – for example, if the market goes below certain interest rates or rises above certain volatility levels. “This allows sales teams to pre-empt changes in the markets and how they might affect clients’ product choices,” says Panesar.
The same AI tools and scenarios can also help with product governance and helping distribution manager reconcile where a fund is registered for sale and where it is actually being sold, and to issue any flags or red alerts whenever there are any discrepancies that could contravene product governance rules.
It is no surprise that asset servicers are so keen on developing distribution analytics services. The demand among asset managers is high and it is the kind of service that offers the high value revenue stream that is so appealing for the service providers given that the core services such as custody and fund administration have become increasingly consolidated.
Not only are the asset servicing banks all competing against one another, there are also the global accountancy firms, the central securities depositaries and the transaction networks all looking to add an analytical angle to the distribution-related services they already provide.
But, says Panesar, DLT is typically more suited to bespoke transactions rather than the mass commoditised nature of the transfer agency process. However, he does agree that the market is “prime for the next technology upgrade”.
And presuming such an upgrade is managed successfully, it should not only produce more efficient transactions at a lower cost, it should also help asset servicers compile an even richer data set and accompanying analytics.
©2018 funds europe