Buyers brief: asset managers must innovate to avoid shakeout

By Aaran Fronda

February 11, 2020 | bobsguide

For more than a decade, the asset management industry has witnessed large-scale consolidation driven by increased margin pressures, as investors continue to shift their savings away from active funds in favour of cheaper passive investment strategies.

This exodus from active funds shows little sign of slowing however, with US passive funds accumulating around $69bn in net inflows year-to-date in June 2019 alone, according to a data compiled by Morningstar.

Another report by PwC claimed that passive funds will achieve parity with their active counterparts as early as 2025, and in that time increased margin pressure, fee compression and escalating outflows will fuel further consolidation, creating a scale game where bigger is not just better but essential for survival.

Inorganic growth requires flexible infrastructure

However, as inorganic growth sees asset management firms continue to grow in order to cope with rising costs, their internal structures have largely stayed the same, with core processes often antiquated and full of friction.

“Transformation and automation are key for mutual fund managers to increase efficiency, lower costs and provide a better client experience,” according to PwC. “By 2025, we expect the front, middle, and back office to be replaced by a single, integrated platform that has been transformed by technology.

“Firms looking to create an integrated platform have two options. One is to build or buy the core technology capabilities and keep them in-house, the other to adopt a multi-platform, cloud-based solution with managers outsourcing some operations to service providers.”

But whatever path firms opt to take it, their success hinges on them having access to high-quality data, especially in a sector where consolidation is rife and timely, cost-efficient post-merger integration is essential to materialise potential synergies, according to Riccardo Lamanna, head of global exchange EMEA at State Street, which offers compliance, risk and data management services to financial institutions.

“[Asset managers] need to focus on data and having a clear enterprise data management model that can be extended easily, while also offering a high degree of flexibility in order to comfortably host additional information and asset inflows,” says Lamanna. “But that is only possible with a solid data management infrastructure behind it.”

However, change on this scale is never easy, especially in an industry as notoriously conservative and risk adverse as asset management, with active fund managers preferring an evolutionary, rather than revolutionary approach to technological innovation. And while it is often better to walk rather than run, time is certainly not on the sector’s side. Thankfully, there are a numerous fintechs and technology companies on hand to help deliver the incremental and even transformational changes the industry so desperately needs in order to navigate the challenges ahead.

Making the right choice

But before progressing with a product or partnering with a fintech or third party, asset managers first need to identify the problems that they are trying to solve, with them usually looking to automate a manual process or enhance an existing one. However, despite the computational capacity and power of machine learning for example, without a clear vision for the application it is ultimately only as good as the hands that wield it. But once a process review is completed, how do asset managers assess which fintechs and software vendors are best suited to for their needs? According to Sandie Lovie, head of global change at Aegon Asset Management, “you just get a feel for the company”, which is easy to do when you work as closely with technology providers as she does.

Over the last 18 months, Lovie and her colleague Derrick Hastie, global head of data technology at Aegon Asset Management, have assessed more than 140 fintechs that are leveraging technologies like artificial intelligence, (AI), natural language processing (NLP), machine learning (ML) and distributed ledger / blockchain technology. Of those, they have chosen to progress with just 14 fintechs, either in a live capacity whereby they are developing a tool or technology with the intention of embedding in into their capabilities or are in a longstanding trial.

“We tend to spend a reasonable amount of time with these organisations before we progress with them,” Lovie says. “We try to understand where they are at in their journey, what they are looking for from us, as some want our help to develop and expand their product, while others already have a fully formed solution.”

Another major consideration for asset managers before purchasing an application is cost. Some products simply aren’t viable for smaller asset management firms regardless of how rich the application is purely from cost-benefit analysis perspective.

As an example, Aegon has been in talks with an AI-driven credit risk analysis tool designed specifically for asset managers. And while the application is rich, especially from a usability perspective, it is simple too expensive for an asset management firm of Aegon’s size, scale and the overall needs, explains Lovie.

Tech giants threaten fund houses

However, when it comes to truly transformational technologies, such as blockchain, which has the power to completely revolutionise the entire asset management value chain, the industry has yet to embrace it, but fails to do so at its peril.

“As an industry, we need to at least start looking at transformational tools like distributed ledger technology, testing them and developing our understanding of them and their relevance for our business,” says Lovie.

“I’m just not sure what the catalyst for transformational change will be, but I fear that the catalyst will come one of the big tech companies like Google and Amazon and, if it does, we will be all sitting there wondering how we allowed that happened.”



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