Investment Managers Are Now Using Artificial Intelligence

Over the past 250 years, technological advancements have been the driving force behind economic and social progress. The most impactful technologies have been those developed for general purposes, such as the steam engine, electricity, internal combustion engine, wire communication, computing, and the internet. These have spurred waves of inventions and applications that have changed the way and pace at which we live our lives beyond recognition. The development of these technologies enabled a shift from the world of Jules Verne’s time, where making a trip around the world in 80 days by using a slow horse and carriage was considered a remarkable achievement affordable only for a few privileged, to the world where millions of people cross oceans in a matter of hours, as a routine.

The significant technology that is being developed in our era is artificial intelligence (AI). Applications in this field are irreversibly changing entire industries. Prominent examples include companies like Amazon, which has disrupted the markets of retail shopping and logistics, and Google, which has changed the way advertising and media sectors operate.

The development of technology for voice recognition has contributed to the application that enables language and speech recognition, which underlies personal assistants like Alexa, assisting with daily tasks. Similarly, developing automation for real-time data analysis allows robots to trade stocks, beat human investors in the stock market game, and compete with other robots. 

The financial world is adopting many artificial intelligence technologies. Today, most payments in the world are made electronically, and credit can be quickly obtained through digital platforms without the need to physically meet a banker. A significant part of the financial world is the domain of savings and investing. This field significantly affects our financial stability and our economic growth opportunities for years to come. The field is developing at an unprecedented pace in opposing directions intended to serve different clientele.

The common principle of AI-based investment systems is that investment decisions should be based on data and not intuition. This is done by collecting information from various sources, analyzing and cross-referencing it in real-time

A simple retail customer, will be directed to a Robo Advisor that classifies the customer into fixed categories, to which a simple, automatic, and passive investment policy is offered without human intervention. For example, an implementation of an investment policy of maintaining a constant ratio of asset allocation between classes (such as stock and debt) in the investment portfolio. This technical rebalancing is done without “smart” considerations that relate to current parameters effecting these assets classes. These basic systems are similar to a system that keeps a vehicle in its lane, but cannot navigate it to an attractive destination or protect the driver from falling into pits along the way. The goal of the Robo Advisor is to enable the major financial service providers to provide basic services to millions of small customers at minimal cost. The price is targeting a very low common standard rather than targeting excellence in investment portfolio management.

Most of the investment strategies offered to the general public are risk-based and have low efficiency in pursuit of specific and accurate investment objectives. Professional investors prefer to implement skill-based investment strategies over those based on risk. Just as we would not imagine going on a road trip without a precise destination, seat belts, and car insurance, professional investors plan their investment goals precisely and protect themselves from potential losses.

Data, Not Intuition

AI-based investment systems enable efficient pursuit of investment goals, using sophisticated and effective tools to reduce risk of loss in the investment portfolio.

The common principle of AI-based investment systems is that investment decisions should be based on data and not intuition. This is done by collecting information from various sources, analyzing and cross-referencing it in real-time. This information includes data on the financial markets, coupled with data on the investor’s personal investment portfolio. Decision-making processes and their execution in real-time are conducted while taking into account various parameters that simultaneously influence the investment outcomes, with complementary processes being developed to embed efficient risk management tools in order to avoid losses.

Major powers invest enormous sums in AI technology development. In 2020 alone, the United States and China invested approximately $65 billion in startups that develop new AI technologies. Israeli players in this field rely on expertise in data analysis developed in the Israeli high-tech sector.

The writer, Alon Tal, is the founder of Alpha Prosperity Funds (a group of fintech companies developing proprietary algo-trading systems and hedge funds management companies).