As high-profile M&As continue, Jeremy Katzeff highlights the data management challenges that come with consolidation.
In August, Goldman Sachs reported stellar Q2 earnings and then acquired the investment management arm of Dutch bank NN Group. The move was part of its long-term strategy to seek out more fee-based business in order to reduce earnings volatility.
The side effect is further consolidation within the asset management industry. But as the buying spree continues, will firms have to pursue consolidation strategies if they want to grow? There are a couple of key challenges that are pushing the industry in this direction, but ultimately it’s how firms utilise data that will determine their success, whether they choose to merge or continue operating as normal.
Fees under pressure
Thinking about the specific challenges, undoubtedly the leading one for firms today is fee pressure. The pressure is being driven by a mix of a continuing low-yield environment being pushed globally by central banks, alongside changing investor preferences that favour low-fee products like index funds and model-driven strategies.
The data on the second point is clear for all to see – US investors have added $605 billion into ETFs in 2021 and despite the academic debate around price discovery with these instruments, the ever-increasing inflows show no signs of stopping.
As a result, the search for scale in asset management continues. While much of this consolidation to date has targeted middle-market boutiques, large organisations are beginning to target other tier 1 and tier 2 firms in a bid to create the size needed to increase fee-earning potential and retain profitability, by benefiting from new clients or new specialities.
The example with Goldman Sachs Asset Management and NN Investment Partners (NNIP) is a case in point. NNIP is a leading tier 1 firm in Europe for ESG [environmental, social and governance] investing, something that Goldman’s board consider to be crucial for growth of their asset management business. NNIP is a specialty investor and thus allows Goldman to gain access to a data infrastructure they would otherwise have to build themselves.
Unsurprisingly, beyond this, we have seen a swathe of recent high-profile deals, including Vanguard and Just Invest, Morgan Stanley and Parametric via Eaton Vance, and BlackRock and Aperio. Looking beneath the surface here, there is also a specific benefit to these deals, as those firms completing the deals look to strengthen their index businesses and incorporate more niche market data to add to their already strong market-leading offering in this field.
As these examples show, ultimately, for most involved in the asset management M&A boom, it’s a data play. These firms want to utilise the vast amounts of data that exists in other institutions and seek out new opportunities in response to the low-fee environment. But while consolidation is additive to earnings and provides lots of data to utilise for the creation of new products and strategies, moving to a data-first operating model becomes a big challenge. And this is what will drive growth in the dawn of the new operating model.
Profitability in the industry today requires more than just size and lots of data. It requires organisational discipline and a data-centric approach to investing and operations. The need for high-quality data across the asset management industry is growing exponentially. Front, middle, and back-office teams need on-demand access to these high-quality data sets to help make investment decisions, launch new products, manage relationships and meet regulatory requirements.
Traditionally, asset management has been slightly behind the curve compared to its sell-side cousins on the deployment and use of quantitative data, whether for trading, research or regulatory compliance. This has changed, and now data is the heart of the asset management operating model.
Sales and marketing teams have been the leaders in a data-driven approach, using numerical insights to monitor and assess the success of the fund’s product promotion. Until recently, the front office has lagged behind, clinging to qualitative investment processes that use the portfolio manager’s ‘secret sauce’ that cannot scale with a growing organisation.
Innovative managers have been adopting new technologies that allow them to take full advantage of a data-first culture. By using data to drive decisions from risk management to asset allocation, trading and product management, clients will have better investment outcomes that meet their long-term investment objectives.
Making consolidation work
Onboarding new organisations will naturally introduce data silos across different parts of the combined entity. With a combination such as Goldman and NNIP, there are also regional implications, given the latter’s set-up in the Netherlands.
Take disparate data sets as a case in point. In order for this data to be used across the different parts of the firm, it needs to be pulled from the different systems that will naturally exist in siloes. This is especially the case within organisations formed as a result of mergers between different entities that are part of larger organisations.
Ultimately the goal for asset managers of all sizes is the same – to effectively integrate data into their research and remain competitive in this fast-changing market. Consolidation may provide opportunities to increase fee-earning potential, but it is crucial they ditch the old operating model, the temptation to keep data in siloes and the spreadsheet approach that underpins this in order to realise this potential.
By moving to a data-centric approach and utilising centralised cloud-based data management systems, the different parts of the fund can work together to offer their unique insight and generate more returns.
Jeremy Katzeff is head of buy-side solutions at GoldenSource
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