Accenture Capital Markets Blog

Asset managers and asset owners, in general, must come to terms with a new environment. Volatility has increased, driven by economic, geopolitical and environmental pressures, and conventional theories on how to generate alpha are increasingly being challenged. This is equally true for sovereign wealth funds (SWFs), which are also facing an additional complexity: Most sovereign investors today are mandated not simply to produce returns but also to be responsible stewards of capital, using their investments to improve their countries and the world at large.

New mandates make for more complex decisions

SWFs and state pension funds are among the largest institutional asset owners in the Asia-Pacific (APAC) and Middle East. The ten largest SWFs across the two regions represent assets in excess of $5 trillion¹. Their role and influence on their national economies is also increasing. In Asia for example, the Singapore government sees Singapore´s Temasek as central to its national growth strategy: its 2021 budget announced a new S$500 million ($370 million) funding platform, to be matched by Temasek, to support investment in large local enterprises and help them tap into new growth opportunities².

Three megatrends for public investors

Such activities on the part of sovereign investors dovetail with three megatrends that are altering the way investors think today. One is industry convergence, the increasingly blurred line between finance, industry and services which is turning large companies more and more into ecosystems. In Singapore, for example, the ride-sharing and food-delivery business Grab has formed a joint venture with the telecommunications company Singtel, to launch a digital bank leveraging the subscriber base of Grab’s super-app³.

The second megatrend is a shift to private equity, amid expectations that public markets might fare less well over the coming decade than the previous one. In February 2021, for example, Malaysia’s Employees Provident Fund launched an Islamic-compliant private-equity fund with three separate managed accounts each worth US$200 million. The fund’s mandate is global and focuses on direct and co-investment strategies into growth and buyout transactions, all monitored to ensure the investments do not violate Islamic strictures either in terms of the activity of the portfolio businesses or lending at interest4.

The third megatrend is investment that improves ESG conditions. Singapore´s Temasek, for example, is seeking net-zero carbon emissions from its portfolio by 2050, and to halve them from 2010 levels by 2030.5

The criticality of data analysis to tackle more complex mandates

The more complex investment mandates outlined above require the access to and analysis of a vast quantity of data—not all of it from conveniently structured sources. Integrating environmental, social and governance (ESG) factors for example is a research-intensive task, and so is investing in private markets. SWFs therefore need a whole new toolkit to ensure that the available data is collected, organised and assessed in the most efficient way possible, so that it can generate the necessary insights for successful investments. However, new technologies could enable SWFs to help deliver deeper, more beneficial data analysis. For example:

  • Data-driven investing: Leading SWFs are increasingly using data-driven models that evaluate investment patterns according to economic and fundamentals-based themes. In addition, the ability to cross-process information from non-traditional sources such social media, video and other forms of unstructured data has strengthened insights for investment themes such as momentum, value, profitability, and sentiment.
  • Portfolio and risk management: Similar techniques can be used to provide SWF investment teams with data and insights to manage risks emanating from portfolio companies, for instance to prevent practices such as “greenwashing” that could undermine ESG investing.
  • Human-machine workforce: The power of AI depends on designing a new workflow that combines humans and automation, so that the latter empowers the former–a delicate transition that benefits from internal champions and building-out6.
  • New ways of teamwork: Large institutional investors could combine specialists in operations, investment, data, finance and legal into one deal team to make better and faster decisions. Internal development clusters likewise bring together the right skillsets and team to drive investment planning.
  • Intelligent processes for corporate functions: Internal administration could be streamlined by leveraging the power of robotic process automation, smart workflows, machine learning/advanced analytics, natural-language generation and cognitive agents.
  • Cloud and cybersecurity: Many major financial institutions are exploiting the scalability of cloud computing, particularly given the “work-anywhere” capability that is necessary today. However, this also requires cybersecurity and cyber-hygiene of equivalent power to protect SWFs’ data.

It is by cracking these data challenges that sovereign investors could fulfil their ESG and national development mandates, and deliver the financial returns expected by their stakeholders in government and the wider public. Leveraging AI, cloud-based scalability and machine-learning could offer not only investment insights, but also demonstrate how portfolio companies can be connected together to unlock new, cleaner growth and value, as true ecosystems that deliver revenue while making the world a better place.

Thanks to Chune Kit Pong for contributing to this blog.