Market Overview

How Individuals Are Using AI, Big Data To Disrupt Retail Investing

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When AI Powered Equity ETF (NYSE: AIEQ) launched late last year, it signified one of the biggest milestones for artificial intelligence in fintech. The AI-powered ETF, a first of its kind in many ways, accumulated over $74m within its first two months of operation, a feat that embodies the ETF’s strong potential for growth.

AIEQ, the brainchild of the investment company, Equbot, uses IBM Watson’s big data processing and machine learning capabilities to process millions of data points every day, helping it construct profitable stock portfolios that rival those by larger, institutional investors.

Equbot’s ETF isn’t the first AI-powered financial product to set its foot in the world of investment. For decades, institutional investors have been using machine learning, deep learning, and other elements of AI to make stock picks. High-flying hedge funds such as Bridgewater Associates and Renaissance Technologies have even become fully dependent on AI, relying on computer-generated analytics for day-to-day market and trading decisions.

Recently, however, retail investors have been digging into AI and big data analytics as signs of an ongoing disruption become apparent. Some of these retail investment managers and individual investors even go as far as integrating top-tier machine learning systems that give larger investors a run for their money.

For many retail investors, AI solutions are more beneficial when developed in-house compared to taking up solutions from third-party vendors such Google and IBM. In-house tools offer sustainability and long-term competitive advantage, especially because solutions by external vendors can be taken up by any investor, killing any hopes for innovation and customized solutions.

Additionally, retail investors are using AI to significantly cut down on costs and time to insight, savings that are passed on to clients in terms of reduced fees and better returns. Mediatrix Capital, an early adopter of machine learning, first went live with its Forex Spot Marketing algorithms in late 2013. In the nearly four years since it first started trading, the retail investment firm has achieved an over-150 percent return. The firm also effectively managed risk across its diverse set of high-yield assets in precious metals and currency.

There’s also Wealthsimple, a popular AI-powered platform that allows everyday investors to invest “on autopilot.” The platform, one of many upcoming robo-advisors, manages over $750m in assets from over 30,000 clients, all of whom have access to AI-powered tools and advice regardless of individual investments.  

Many others in the space trying to solve the problem of access, a major impediment to the adoption of AI in retail investment. “Access, combined with risk and fear of the unknown, has always been responsible for the low number of retail and individual investors using intelligent tools in finance and investment,” says Henry Jenkins, a personal finance consultant and founder of the online platform Auto Loan Source.  

Many of these upcoming AI-powered platforms, Jenkins says, have the potential to transform the game, largely because they empower novice investors with the knowledge of strategy. Many of these platforms, including Equbot’s intelligent ETF, have a way of tracing back their decisions to some rational premise, which makes them understandable to humans—unlike the bigger, complex systems by institutional investors.

At the end of the day, AI and big data will undoubtedly disrupt traditional investment strategies in the retail niche. For retail investors and portfolio managers, these it mean leaner business processes and better decisions.

The preceding article is from one of our external contributors. It does not represent the opinion of Benzinga and has not been edited.

Posted-In: contributor contributorsFinancial Advisors News Hedge Funds Personal Finance General

 

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