In the last few years, AI Has been responsible for the transformation of multiple fields, coupled with the increasing efficiency of using improved datasets. One such area in which AI has excelled in is Robo Advisory which is a field that has an extensive amount of financial big data to analyse.
Robo-advisors are AI built systems that use algorithms to automatically perform investment decisions or tasks which are originally done by humans. “Robo advisors are a potential solution to the complexities of financial decision making,” said Jill E. Fisch, a law professor at the University of Pennsylvania at a conference for the Pension Research Council.
The concept is that robo-advisors are merging information from customers including their financial goals, risk tolerances, timeframes, with the appropriate allocation of assets that qualifies customer’s needs. During the merging process, they use numerous algorithms, including machine learning models in order to develop the best fit for the customer. They take a lot of action during the process, such as rebalancing the portfolio and performing tax-loss harvesting. This aims to increase efficiency while taking decisions at the right time, guided by the portfolio.
Large numbers of businesses have begun to use AI in the robo-advisory field. New York investment firm, Betterment is one enterprise that has adopted the use of robo-advisors to reduce the taxes on transactions where machine learning algorithms select the specific tax consequences of the transactions. Much the same, SigFig, also incorporates AI to assign assets and decides which investments will result in minimum taxes.
Another firm that uses AI is Wealthfront. Adam Nash, former President and CEO says that, “We’re firm believers that artificial intelligence applied to your actual behavior will provide far more powerful advice than what traditional advisors offer today.”
Fidelity is another firm which started its robo-advisory service in 2016, named Fidelity Go. At the beginning of last year, Fidelity Go was the highest ranking best overall robo-advisor in the 2019 winter edition of The Robo Ranking report from Backend Benchmarking.
One of the biggest impacts of AI might be that it saves time for human advisors. AI has increasingly more advanced deep learning capabilities which takes the stress away from advisors which would ordinarily have to perform much more mundane and laborious monitoring tasks. When allocations fall outside of certain criteria for specific customers, an AI-based system can trigger it into the direction of a human advisor.
In order to raise efficiency AI needs substantial amounts of data to provide more accurate results. “Analysis of vast quantities of historical and financial data will uncover alpha opportunities that traditional analysis would otherwise overlook and give robo-advisors an edge over passive strategies and AI can process big data swiftly, allowing robo-advisors to adapt to changing market conditions and consumer behaviors much quicker in order to make better investment decisions. Time saved is key here,” says John Zhang, founder of a robo-advisory startup WealthGap, which explores AI in hedge fund-like portfolios.