Nand Kishor Contributor

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...

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Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...

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How Big Data and Artificial Intelligence Affect Investing

By Nand Kishor |Email | Jun 30, 2017 | 6936 Views

Retail investors do not always have adequate time to research opportunities for making money. Fortunately, the rise of big data and artificial intelligence (AI) is helping individual investors make more informed investment choices.

Access to Data Mining
Due to the increase in data mining becoming available for the public, investors can gain information and insights in the marketplace that were formerly available only to institutional investors. Many investors believe that Wall Street was hesitant to accept making big data available to the public because it posed a potential threat to the ways many investment firms make money. If retail investors are able to gain the same facts and financial forecasts as institutional investors, individuals may perform more of the work themselves rather than utilizing the firms' services, resulting in substantial losses.

Personalizing Investment Services
Because of big data, the financial industry is learning how to get closer to investors and learn about each client's portfolio, needs and objectives for a more personalized service. For example, rather than simply selling financial products and making money, advisors must explain investment opportunities that best suit each client's objectives so that clients understand the basis for investing and the potential for earning money.

Due to the rise of gaming engaging people's minds for long time periods, similar technology will be used to engage investors digitally. More mobile applications will be available for researching, buying and selling investments. More opportunities for wealth creation will become available as the financial industry shifts its focus from largely middle-class males to a much more varied client base.

Artificial Intelligence and Trading
Algorithmic trading comprises approximately 70% of trades made on worldwide exchanges daily. Because of this, after 167 years of trading, the Chicago Mercantile Exchange Group closed most of its doors in 2016 because traders were rapidly being replaced by AI. Also, approximately 75% of trades on the New York Stock Exchange (NYSE) and National Association of Securities Dealers Automated Quotations System (NASDAQ) are performed by machines, which may lead to further job losses.

AI continually gains more experience and digests more information as it operates, potentially allowing machines to outperform humans. For example, Goldman Sachs uses AI for analyzing big data and how weather, news and events impact financial markets. Also, approximately 40% of hedge funds launched in 2015 used AI for making investment decisions. In addition, for the past seven years, funds based on AI have often outperformed equities and other funds. Hedge funds that failed to outperform other funds learned how to improve based on their mistakes.

Replacement of Financial Analysts
Many investors believe that AI will take the place of investment analysts. Because analysts spend hours collecting and analyzing data, and AI can perform those functions in minutes, much time and money is saved by using machines. Also, humans take time to evolve and learn from their mistakes, whereas AI may correct its errors in minutes. In addition, humans may be slow to adapt to changing market conditions, whereas machines adapt quickly and without human input.

Brokerage Firms and Artificial Intelligence
Many brokerage companies supply client information to machines for better portfolio management. Each investor's income, risk profile, expected return and other details are entered into a computer. The software creates a selection of appropriate investments and manages them daily.

Benefits of Artificial Intelligence
Retail investors may save time and money utilizing AI for investing rather than paying personal advisors to research, select and manage their portfolios. Also, funds chosen by a machine do not have the management costs typically charged by investment firms. In addition, because AI can place trades in less than one second, computers can exploit small changes in stock prices or indexes to bring in more profit. Furthermore, machines do not understand greed or fear, meaning they are unlikely to sell when the market is down or buy when the market is up.

The Bottom Line
Big data and AI appear to be here to stay. Through continued use and improvement, the two are likely to continue improving how retail investors grow their money and shape the future of the financial sector.

Source: Investopedia