The asset management industry remains a prime target for digital disruption, according to “The future of funds: How the asset management industry must evolve for the digital future” whitepaper by HSBC and Northern Trust.
There has been a variety of core capabilities and data driven progress achieved over recent years, which was further propelled by the COVID pandemic.
“Some aspects of this experience have fast-tracked progress in digital-first capabilities and interactions in ways not thought possible at scale in past years,” commented Justin Chapman, Global Head of Digital Assets, Northern Trust.
“Previous to this, legacy digitalisation projects have dragged on with paper and fax-based interactions remaining in place in some pockets of the value chain and much longer than they should have been,” he added.
Chapman said that the eradication of these elements provides the foundational layer for digital-forward innovation to build on in the coming years.
According to the whitepaper, there are a range of digital innovation opportunities suited for different fund types – for example master-feeder funds can benefit from streamlined and automated processes, which improves transparency and communication between the master fund and its feeders.
“From core digitisation across the tech stack, to the emergence of early digital token fund unit representation, the signs are clear that a watershed moment in progress is a matter of when and not if, as bigger institutional firm focus centres on the next wave of adoption and product,” Chapman said.
The paper outlined a number of options for fund managers looking to realise some benefits of blockchain technology, while minimising complexity and allowing for ease of adoption.
One option for fund managers is tokenising the units of a fund, whereas another option is tokenization of underlying assets of a fund.
The paper highlighted four key contributing factors that can influence the “shape of that future and increase the velocity of that progress”, namely: Tokenisation of Asset and Cash; Integration of ESG; Platform business models; as well as Artificial Intelligence (AI) and Machine Learning (ML).
Chapman said that the relevance of a platform model becomes especially clear in both the administration and distribution of fund, adding that DLT enabled shared networks are one possibility for how the platform model can evolve: “A key consideration for this model is facilitating access and participation on the platform”.
The whitepaper stated that AI has experienced a surge in growth over the past few years.
AI-driven algorithms have the ability to analyse massive datasets. Using machine learning (ML) toolsets over that data to structure and learn can benefit functions such as streamlining portfolio construction by optimising asset allocation based on various parameters, the paper said.
“As AI continues to advance, its role within funds will likely become even more pronounced, reshaping how funds are established, operated, and optimised to meet investors’ evolving needs and expectations,” Chapman noted.
He further said that there is undoubtedly momentum building across the funds tokenisation landscape.
“Investor preferences and expectations continue to evolve as fast, if not faster, than the technological advances before us,” he said.
Champan also said that there is no escaping the practical realities and headwinds to making progress, while navigating the capital investment required, regulatory uncertainty, cross-border barriers, backward compatibility and maintaining current operating models in co-existence. “This is not a space that will see success in isolation. Collaboration will remain key,” he concluded.
