Types of artificial intelligence applied to investment

2 min. reading
Artificial Intelligence / 2 October, 2021

Karla García Gil Journalist

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The revolution brought about by Artificial Intelligence (AI) represents an unprecedented competitive advantage and, when applied to the investment field, opens up a wide range of possibilities. The investment process, from research to analysis to decision-making, has benefited from this technology in recent years.

Investment management firms are gradually moving away from models that still require human intervention to AI models capable of analyzing large volumes of data.

Some examples of these technologies are as follows:

History of artificial intelligence

History of artificial intelligence

In 1854, the British mathematician George Boole argued that logical behavior can be represented and expressed mathematically, as in a system of equations. Far ahead of his time, this thinking is what has earned him consideration as the forerunner of today's computational sciences.

  1. Machine learning

This refers to the automatic learning capacity of a machine or software and one of the techniques it provides is Sentiment Mining (sentiment analysis), which can be applied to the latest publications of banks and even to the financial news of newspapers, and thus, regularly observe what is the implicit pattern in the texts, in a quantifiable and systematized way.

Thanks to this, market prices are contrasted against the levels of other assets and it is possible to forecast which are the best decisions in the construction of a portfolio, according to the current moment and the exact type of investor.

  1. Robo-Advisor 

It is a digital financial advisor operated through a FinTech company, which offers automated financial planning, with the advantage of requiring minimal supervision by humans. Robo-advisors monitor markets on an uninterrupted basis and represent up to 70% savings for investors.

In addition, such technology can help with simple practices such as opening accounts and transferring assets. The process starts with a questionnaire that clients must answer about their investment appetite, risk and liquidity factors, data that robo-advisors translate into investment logic.

  1. High Frequency Trading (HFT)

It is an automated high-frequency trading platform that involves specialized software and algorithms, high-end computers and low-latency internet.

It is used by large financial institutions since it performs transactions at high speeds, allowing traders to execute millions of trades and detect emerging trends in a matter of seconds, which provides a great advantage in the market as it enables strategies that would otherwise not be possible.

High-frequency trading has existed long before cryptocurrency and accounts for up to 80% of volume in certain asset markets.

  1. Virtual assistants

They assist the client in making financial decisions and support banking operations, and provide detailed information on accounts, balances and movements without the need to install applications.

The technologies behind virtual assistants analyze and process machine learning, language processing and voice recognition. Thus, as the customer interacts with their virtual assistant, AI programming uses algorithms to learn from that data and improve prediction of their needs.

The importance of Artificial Intelligence applied to investment lies in the fact that the tools it offers allow early and timely decisions to be made in order to build better strategies. AI helps to process a vast amount of information and from it, generate patterns and conclusions that help investors and/or companies.



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