Whatever the different ways wealth and asset managers seek to grow, one factor appears clear: it is vital for firms to get their data foundations as solid as possible. That's the message from this guest article from Ernst & Young Advisory Pte.

The following article, from Han Wee Tan, partner, wealth and asset management consulting for Enst & Young Advisory Pte Ltd, addresses the issue of managing data to help wealth firms navigate tough market and business conditions. The author is based in Singapore. 

The editors of this news service are pleased to share this article and comments; the usual disclaimers apply to views of guest writers. To respond, email tom.burroughes@wealthbriefing.com

Given the current economic backdrop and volatile market environment, more asset managers are focusing on being nimble and agile by investing in technology and data to improve operational efficiency and drive growth. 

This reflects a transformational shift in the way that investment firms and asset managers approach technology: rather than shying away from innovation, they are embracing it wholeheartedly and setting data agendas to harness its potential.

While there are various strategies employed across the wealth asset management sector, one thing has become clear: it is essential for companies to invest in a solid data foundation to drive effective digital transformation.

As asset managers consider investing in operational efficiency, a well-thought-out plan anchored on data defence (ensuring data quality and security) and data offence (using data for investment strategies and market insights) will be critical. 

A well-constructed data agenda will account for both types of data strategies and ways in which the business can scale up to meet their goals. At the same time, asset managers – especially larger ones with a global presence – need to look at their operating models, prioritise optimising speed and flexibility in local markets, whilst building horizontal data platforms that bring efficiency at a global scale.

Many in the industry have already recognised the importance of accurate and reliable data for future growth and technology-driven initiatives. As investment firms double down on how to leverage data and technology for competitive advantage, many have also onboarded data scientists and technologists onto their investment teams, adopting modern technologies and tools to drive investment and operational alpha.

At a hygiene level, asset managers must establish a strong data layer that ensures accuracy and transparency in areas such as cash positions and exposures. These are critical foundations for optimal investment decision-making. 

At the same time, digital upskilling should not be ignored. Asset managers have been focusing on the professional development of business users who are fluent and skilled in using programming languages such as SQL and Python and other critical know-how to maximise return-on-investment (ROI) in technology platforms. 

With the speed of technological processes today, there is a fine balance between focusing on innovation and maintaining operational stability. Both of these should be viewed as complementary for long-term success, with asset managers learning to experiment and fail quickly, instead of using the traditional implementation approach of trying to get things perfect the first time.

Turning to generative AI, asset managers are already well aware of the unlimited potential it might have, in theory. However, current use cases are limited in demonstrating its future prospects and, in reality, firms are mostly relying on it for automation purposes and to take on more day-to-day routine tasks. 

AI still warrants investment and companies understand this. However, the industry recognises that it is still nascent and will move more into a stage of general use cases where machines can bring forth insights and actions based on huge volumes of data, for example across portfolio management, back-room processes, and customer intelligence to provide higher levels of insight. According to the latest EY report on AI adoption (Generative AI in wealth and asset management), 50 per cent of respondents believe that over 11 per cent of their back office operations would be directly impacted by Gen AI.

In summary, to compete in the market today, asset managers need to have a solid data foundation in place, embrace digital cultures, and learn to try and fail fast to balance innovation and risk management. Whilst AI is in its nascent stages today, future technological innovations that surpass humankind's current imagination may be on the horizon. By investing in critical enabling technologies and data today, asset managers can be better placed to tap on those disruptive forces when they come along. 

The views reflected in this article are the views of the author and do not necessarily reflect the views of the global EY organisation or its member firms.