BLOG. 4 min read
As technology continues to become more automated, the risk of quantitative trading, robo-advisory, or market surveillance algorithms replacing banking jobs is a great threat to Wall Street and others in the financial services industry. Rep. Bill Foster of Wells Fargo predicts that 200,000 banking jobs in the U.S. will be lost over the next decade due to the introduction of new technologies (Rundle 1). These new technologies include Artificial Intelligence, Machine Learning, cloud-based analytical software, and much more. However, the implementation of these technologies is not the only reason why AI is taking over Wall Street. According to Professor Marcos Lopez de Prado, “Financial machine learning creates a number of challenges for the over six million people employed in the finance and insurance industry, many of whom will lose their jobs, not necessarily because they are replaced by machines, but because they are not trained to work alongside algorithms.” The adaptation of this advanced technology can only be as advanced as those who are capable of utilizing it efficiently. If a machine learning or cloud-based approach is implemented without proper training or qualified employees, there is a risk of algorithmic glitches that can lead to market manipulations, failure of proprietary software, or misguiding clients.
The most notable time when algorithmic trading dramatically manipulated the market was the Flash Crash of 2010. On May 6, 2010, the stock market suffered a trillion-dollar crash within 36 minutes before rebounding 70% by the end of the day. Since then, global exchanges like the New York Stock Exchange and Nasdaq have enforced market-wide circuit breakers that trigger a pause if declines exceed around 10% from its previous close or a complete stop in trading activity if declines exceed 20% from its previous close. This helps mitigate the risks of flash crashes occurring but does not eliminate the possibility, especially as high-frequency trading algorithms begin to dominate Wall Street. In a survey conducted with more than 3,800 respondents of CFA Institute members and candidates, 43% believe that their roles will change significantly within the next 5-10 years and that the three roles most likely to disappear are sales agents, traders and performance analysts (Fender 2). In order to adapt to advancements in technology, it is critical that companies develop training programs for employees to work alongside these algorithms.
In addition to the abundant amount of free online courses through Coursera or edX, many companies have developed their own internal learning platform to teach employees about company-specific processes or general courses. For example, the SS&C Learning Institute offers 322 online courses and 235 video lectures available to all employees through SS&C Learning. These courses range from a mix of general information to specific training on the various types of business units at SS&C. Despite all of the available information on the internet relating to advanced technology, not everyone knows Coursera offers free courses on Introduction to Artificial Intelligence (AI) through IBM or Machine Learning through Stanford University. It is the responsibility of a company to provide this information in an easily accessible format to their employees or they will struggle to keep up with competitors in their industry due to the potential for high turnover, low retention rates and general inefficiencies when using new technology.
If in-house training is not a possibility, outsourcing data analytics to a fund administrator can save valuable time that could be utilized in other areas of your business. SS&C Alogrithmics Workspace Analyzer provides a highly flexible analysis and reporting solution designed to quickly and efficiently integrate with your existing infrastructure. This integrated reporting tool includes optional add-ons for FRTB, SA-CCR, market risk, and ALM and liquidity risk.
If you are interested in learning more about SS&C Algorithmics, visit our product page.
Flash Crash image (Source Wikipedia):
Sources:
Fender, Rebecca. “Hearing: ‘Robots on Wall Street: The Impact of AI on Capital Markets and Jobs in the Financial Services Industry.’” Testimony to the House Committee on Financial Services Task Force on Artificial Intelligence, U.S. House Committee on Financial Services, 6 Dec. 2019, financialservices.house.gov/uploadedfiles/hhrg-116-ba00-wstate-fenderr-20191206.pdf.
Kenton, Will. “Flash Crash Definition.” Investopedia, Investopedia, 18 Nov. 2019, www.investopedia.com/terms/f/flash-crash.asp.
Rundle, James. “Wall Street Braces for Impact of AI.” The Wall Street Journal, Dow Jones & Company, 9 Dec. 2019, www.wsj.com/articles/wall-street-braces-for-impact-of-ai-11575887402.
Links:
https://www.coursera.org/
https://www.edx.org/
https://financialservices.house.gov/uploadedfiles/hhrg-116-ba00-wstate-fenderr-20191206.pdf
https://www.investopedia.com/terms/f/flash-crash.asp
https://www.ssctech.com/landing/ssc-algorithmics
https://www.wsj.com/articles/wall-street-braces-for-impact-of-ai-11575887402
