In the 'data is king' era, investment managers must modernise with AI and blockchain or risk obsolescence, writes Simon Brown, senior vice president, head of alpha platform sales, State Street EMEA.
The future of investment will be interactive. Investment managers and asset allocators will be expected to answer questions in real time, drill down to any level of detail, access data from multiple domains – all in a few clicks. As AI continues to develop and mature these use cases will become pervasive within capital markets. As the financial services industry evolves in an era when data is king, asset managers and allocators yet to prepare their operating model in an era when 'data is king' will be at serious risk.
The challenges institutional investors face are complex, although they can be boiled down to one word: data. In a sea of massively growing data volumes and interlaced networks of data sources, cloud-based AI technology with a high degree of flexibility will help all participants across capital markets unlock new capabilities.
The challenge Market events over the past few years have shone a bright light on the investment processes employed by institutional investors. The macro environment, liquidity shocks and volatility amongst other factors, meant firms need to focus on stabilising flows as events arise, while implementing their growth agendas in an increasingly competitive market while under escalating fee pressures.
On the other hand, pension funds, family offices, sovereign wealth funds and other allocators have been actively seeking to diversify their portfolio into private assets, which in turn increases the regulatory requirements on reporting, transparency and liquidity.
Although some manage a portion of their portfolio internally, asset allocators traditionally outsource their day-to-day investment management to multiple external asset managers and service providers. This reliance leads to information lag, which is no longer acceptable to their investment boards or regulators and can create acute challenges in a crisis like the UK liquidity crisis in late 2022. Allocators need access to accurate and timely data on holdings, investable cash and positions to quickly invest new funds, rebalance allocations and identify counterparty exposures.
Additionally, as demand for transparency increases and the need to make timelier and better-informed allocations has become more important, asset allocators’ roles have expanded beyond supporting portfolio management, risk modelling and trading. Many allocators are now evaluating their operating models to bring higher value-add activities in-house to support growth and optimise budgets.
For asset managers, data challenges are often a product of complex and fragmented infrastructure that was created or acquired over the years to serve individual investment teams. This patchwork of disparate systems and data sources, which are complex and expensive to manage and maintain, create a significant “technology debt”. In addition, asset managers must adapt to increasingly complex regulatory changes in different markets, ensuring their relevance and appeal to increasingly sophisticated and digitally savvy end-investors.
The opportunityDespite these challenges, the 'data is king' era presents ample opportunities. What is required is a solution that addresses the shortcomings posed by a patchwork of legacy systems. A centralised data repository can capture, leverage and validate the massive volumes of underlying data and analytics from multiple internal and external sources across the enterprise and investment lifecycle. A strong data foundation is both the first and the most important step to enabling AI capabilities; without this foundation, AI will simply produce very pretty results that look accurate but are subject to the same flaws as the data it is leveraging.
Those at the forefront of this transformation are well positioned to benefit from the significant advances in AI, machine learning and blockchain-based tokenisation. Deep learning algorithms detect anomalies in data, while trade desks are mining order and execution history and predictive algorithms to make smarter decisions around venue and broker selection, lowering trading costs and demonstrating best execution to their clients.
Blockchain serves as a natural complement to AI, providing greater transparency and auditability of AI-based decisions. Additionally, tokenisation will democratise access to private markets for retail investors, an asset class that was typically only available to HNW and institutional investors. Finally, customised large language models are being trained to provide natural language, self-service capabilities to investment professionals looking to gain deeper data insights – democratising the ability to analyse data at scale.
Building solid foundationsThe current environment presents us with interesting challenges and opportunities. Those firms that move quickly to create a single, trusted source of truth within their organisation – one wrapped with modern cloud capabilities to provide low friction access to teams and systems – will be best placed for the future.
Without a solid foundation, those left behind will face a vicious cycle: more time and cost spent fighting fires resulting in less time to invest in the foundation required to take advantage of the opportunities. In an era where 'data is king', the time to act is now.
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