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Artificial Intelligence Replacing Humans on Wall Street, and COVID-19’s Impact

· Coronavirus,Automation,Employment,Economic Trends

Artificial Intelligence Replacing Humans on Wall Street, and COVID-19’s Impact

Advancements in artificial intelligence are constantly putting jobs in jeopardy of becoming obsolete, including employment in the financial services industry. Rep. Bill Foster (D., Ill.), chairman of the AI taskforce, cited a report from Wells Fargo & Co. that predicts around 200,000 banking jobs in the U.S. will be lost as new AI technologies are introduced in the next decade.

But the key distinction to make here is that jobs in the financial services industry are at risk of being lost not due to obsolescence in the face of AI, but due to the workforce’s inability to work alongside new AI technologies and algorithms.

Many roles in Wall Street, such as investment banking teams working on closing M&A deals, cannot exist without human interaction and cooperation. After all, businesses are man made creations that live and breathe just as we do.

Jack Kelly of Forbes mentions how investment banks such as Goldman Sachs are beginning to seek workers who possess math, technology, software, coding, and data analytics related skills so that AI technology can be utilized to improve human efficiency. But the rising dominance of AI technology in sectors such as sales and trading and asset management cannot be ignored.

The most significant advantage AI technology presents is the elimination of human bias and error in any financial decision-making process. Kelly mentions how Nasdaq has a regulatory body coded with over 40 algorithms, using around 35,000 parameters to spot possible cases of market abuse and manipulation in real-time.

This role – namely surveillance – is where the incorporation of developed AI technologies can shine, because such technologies can track market data and millions of trading activities with accuracy and efficiency that even the most experienced figures in the financial services industry cannot match. In addition, it is also cost and time-efficient, which is why the majority of the New York Stock Exchange floor is filled with technological gear conducting digital trading activities rather than humans.

In the asset management sector, the development of AI technologies has also resulted in the increased popularity of robo-advisors. These online platforms that offer financial advice and investment management based on mathematical rules/algorithms with minimal human intervention.

By automating financial planning, robo-advisors can combat the behavioral weaknesses of wealth management advisors that may be too aggressive, while also offering a minimal cost solution. In a study on the awareness and perception of Robo Advisory Services among investors in Pune City, the study survey highlighted that investors in high-income groups with investable assets of above 2.5 Lakhs ($2.7 million) were not willing to use Robo Advisory services when making investment decisions.

However, 39% of investors in medium-income groups with investible assets between 5 ($541,000) to 10 Lakhs ($1.08 million) were either already using or willing to use Robo advisory services to make investment decisions. Overall, the study found that most retail investors needed professional advice to improve their portfolio yields, which is why the future of AI in wealth management is very bright – because it is a cost-efficient, safe, and effective alternative.

Surely, experienced fund managers and long-standing members of Wall Street may express skepticism towards this shift, since AI technology is often portrayed as a weapon that must be controlled precisely by experts. Even Elon Musk, the co-founder of OpenAI, has expressed his concerns regarding AI numerous times, saying that such technology could potentially be “more dangerous than nukes” and that organizations developing advanced AI should be closely monitored and regulated by the government.

However, we may see AI technology penetrate Wall Street even faster now due to the Coronavirus pandemic. The WSJ recently reported that the AI Company ForgeRock raised $93.5 million in funding, with demand for its machine learning technology skyrocketing as the Coronavirus shifts the workforce towards working remotely.

ForgeRock uses machine learning to validate one’s identity and detect potential fraud, and the company has over 1,100 business partners spanning from sectors such as finance to retail to government. Though ForgeRock announced it would use its latest funding to improve its machine-learning algorithms for online sign-in processing, the principle at hand is that our reliance on AI technology during socially distant times is heavily increased.

During this pandemic, as financial services firms experience hard hits on capital inflows and low interest rates, the most significant realization will be that the most expensive costs banks have to face are their employees. One of the most promising solutions for the future may be to invest in artificial intelligence to cut costs, which is why we may see companies such as ForgeRock begin to expand the capabilities of their technology beyond IT and surveillance.

In fact, this trend has been noticeable, especially in the past couple of years. Vasant Dhar, founder of the $350 million Adaptive Quant Trading program at SCT Capital Management, stated that “machine learning is showing it can get ahead of the passive wave and exploit patterns in markets that haven’t been discovered.” Investors have been buying into these claims – assets in quant funds (many of which use AI) surged by 86% to $940 billion since 2010.

At maximum levels of integration, AI technology can become a dominant part of Wall Street’s identity in the next decade - and with the Coronavirus pressuring banks to cut costs and find alternatives, this may happen sooner than expected. But at the core, artificial intelligence is likely to remain as a sidekick to experienced figures in the financial services industry.

While the technology can take charge of tasks that make up for human inefficiencies – unemotional investment decisions, automated market surveillance, and rapid-fire number-crunching tasks – it will never have the perception and intuition of financial experts that will always be critical in financial decision making, as well as the human ability to take historical crises into context and apply lessons learned.

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Written by Glen Oh, Edited by Jack Argiro & Alexander Fleiss

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