Asset Management: The Human vs. The Machine

Asset Management: The Human vs. The Machine

As Niels Bohr said “prediction is very difficult, especially if it’s about the future”. The exact future of the asset management industry isn’t clear, but there is a strong belief as to where it is headed. Traditionally, investment management has been an active, hands-on industry built upon human interaction and trust. In the 80s and 90s investment professionals would spend their days doing in depth research to receive an acceptable 2% fee for their performance. This, of course, being a time where the market had annual returns around 14% and few cheaper alternatives. Now, an increase in efficiency due to technology and prevalence of passive investment options are changing the industry. Today, this traditional landscape is unfathomable with the increase in low-fee passive strategies and transparency. As of 2013 passive investments surpassed $1 trillion dollars, yet investors still had $3 trillion in active funds hopeful that their managers will outperform the benchmark. Active being funds that are managed by a human investment professional who tries to outperform a benchmark and passive being a benchmark matching fund with little to no human intervention. PricewaterhouseCoopers estimates that by the year 2020 35% of the industry will be composed of passive investments and alternatives. These passive strategies come with low fees due to the fact that most of the trading and analysis is done by algorithms and computers.  This trend puts active managers in a difficult predicament to justify fee structures in an investment environment where it is challenging to outperform.  

Unfortunately, this dynamic change doesn’t end there, an increase in artificial intelligence (AI) in the coming years will revolutionize the industry unlike ever before. Artificial intelligence is a relativity old concept but has recently injected itself into a variety of industries. The technology itself gives computers the ability to learn and adapt without being constantly reprogrammed. Machine learning has been a laggard in the financial services industry and is just recently starting to make a noticeable impact in efficiency and costs. The applications of such technologies are nearly endless. AI can analyze macro data sets to recognize trends and develop new strategies, it can send alerts to investors if an event impacts their portfolio and recommend a course of action. Beyond the investment implementation, it can even currently be used for customer support, trade processing, compliance and enterprise management.  

Every breakthrough in technology leads to a task becoming obsolete; why pay someone to do what a computer can do?  Of course AI can’t take over every job in the asset management industry, but it can disrupt some. Of the 230,000 financial services jobs estimated to be replaced by technology by the year 2025, 90,000 are expected to be in the asset management industry.  A lot of these expected to be back office, operations and customer service jobs as told by consulting firm Opimas. This shift in the job environment will lead to more jobs in data analytics and computer science in the asset management as well as fewer traditional roles. Although technology may disrupt some of the current positions, it does provide two main benefits. Firstly, AI’s time saving ability gives employees the option to work on more pressing matters to find added-value for clients. Secondly, AI may take some work but at the same time is generates different work that may not have been available beforehand.

In conclusion, AI must not be something we are intimidated by, but something we embrace. To remain competitive, asset managers must be a step ahead in integrating this effective and time saving technology into their business plan. Many asset management firms are focused on “Big Data” and machine learning but, the fact remains that past results are no guarantee of future performance. AI may be able to more quickly interpret data and “learn” from it but, human interaction and interpretation of both machine generated analysis and client objectives have a place in the investment process for the foreseeable future.

 

 

Acton, Gemma. “We’re seeing how far we can push artificial intelligence in asset management: Man Group’s Lagrange” CNBC.com. https://www.cnbc.com/2017/05/17/were-seeing-how-far-we-can-push-artificial-intelligence-in-asset-management-man-groups-lagrange.html. (accessed January 1 2018).

Appatura. “3 Ways That AI Will Impact Mutual Funds and Asset Management” appatura.com. https://www.appatura.com/3-ways-ai-will-impact-mutual-funds-asset-management/. (accessed January 1 2018).

Marriage, Madison. “Fund Managers Deny AI Threatens Jobs” Financial Times. https://www.ft.com/content/bd26af40-7dd9-11e7-ab01-a13271d1ee9c. (accessed January 1 2018).

PWC. “Asset Management 2020: A Brave New World” PWC.com. https://www.pwc.com/gx/en/industries/financial-services/asset-management/publications/asset-management-2020-a-brave-new-world.html. (accessed January 1 2018).

 

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