John Lanaro, Global Head of ETFs at RIMES
When Exchange-Traded Funds (ETFs) were developed in the 1990s the aim was to provide individual investors with access to passive indexed funds. However, as ETF investing has risen in popularity, the nature of the funds have evolved.
Today, in addition to traditional, passive ETFs, investors can place their money in thematic ETFs and/or active ETFs. Both options look extremely attractive.
The ETF boom
Thematic ETFs, as the name suggests, track funds that are tied to a specific theme, such as artificial intelligence or renewables. Last year, thematic ETFs performed very well – 33 of the 36 European-listed thematic ETFs significantly outperformed the MSCI World Index – and as a result attracted €9.5 billion in net new assets in Europe alone. This year, they are maintaining this winning streak, with 70% of thematic ETFs in Europe having outperformed global equities in the year up to May.
Active ETFs, in which fund managers buy assets without following an index, are also experiencing a boom. According to data from TrackInsight, twenty-two new ETF issuers have already come to market this year, a surge that is in part fuelled by legal changes in the US which make it easier for fund managers to conceal their decision making from competitors. Active strategies are also inherently preferable to asset managers as they command higher fees than passive alternatives.
The data challenge
However, the very proliferation of ETFs that marks out this booming market is also a significant challenge for investment firms. The vast and growing number of ETFs represent a deluge of data that firms must master if they are to understand the true risk exposure of each ETF.
At present, there is no standardisation when it comes to the file formats or data delivery channels used for ETFs. That means ETF data must be sourced, normalised and validated on a case-by-case basis – before the underlying composition data can be analysed for insights into risk and performance. With every new thematic ETF, the more challenging this task becomes.
Active ETFs bring with them additional data management challenges. While active ETFs do not aim to mirror the performance of indexes, fund managers do need visibility into market conditions to make intraday asset allocations that will, they hope, deliver alpha. These firms therefore need timely visibility of any relevant index data, as well as validated daily ETF composition and reference data on which to base their investment decisions.
So, although active and thematic ETFs offer investment managers significant opportunities, they also require commitment to data management practices that are ultimately non-core. This is why outsourcing such activities increasingly makes sense.
The appeal of outsourcing
When it comes to investment management, firms have traditionally shied away from outsourcing their operational data. They pay for the data licenses, and so feel they should retain control of the data. However, as data volume and complexity increases the economics and value of managing that data in-house shifts.
Outsourcers bring with them economies of scale, as well as the direct relationships with ETF issuers. What’s more, data manifestly is the core of outsourcers’ business: they have invested in the technology, processes and people needed to streamline and optimise data management.
The benefits of the approach applied to the ETF space are clear. The first is quality and accuracy. Data management outsourcers can provide quality-assured, decomposed data so that firms can instantly see their true risk exposure. The second is velocity. One of the core benefits of ETFs is that they can be traded intraday. The timelier your data, the better able you are to manage active funds. Moreover, thanks to their close relationships with data providers, data management outsourcers can also enable quick access to new ETFs as they come online, along with the seamless integration of new file formats.
The competitive choice
The fruits of active and themed ETFs mean most asset managers will look to incorporate them in their portfolios. They have two options in doing so: manage the data in-house, or outsource it to experts. The latter approach frees up internal resources from non-core data wrangling so they can focus on what is core: finding alpha or selecting the investment themes that will deliver the best returns or best meet the client mandate. It’s an approach that reduces the complexity of the ETF space and which will deliver a significant competitive advantage to those who employ it.
