The Future of Investing: How Artificial Intelligence is Changing the Game

Where is AI Now & Where Is It Headed?

Artificial Intelligence, or AI has come a long way from its origins as a science fiction motif and is rapidly becoming an integral part of our everyday lives. From the seemingly simple task of directing a Roomba vacuum, to the more sophisticated application of Natural Language Processing, AI is quickly revealing its potential and has been praised by many experts as a pinnacle of innovation.

While AI is being developed in a wide range of sectors — from autonomous driving to healthcare — the potential use cases of AI in fintech are particularly exciting. As it currently stands, AI is still an emerging technology, but in analyzing its potential, AI holds the potential to revolutionize the industry and greatly impact individual investors and large institutions alike. Imagine having a super quantum computer that could trade on the stock market entirely on your behalf using advanced market knowledge coupled with sophisticated algorithms, and make 10 percent returns every hour on the hour! Well, we’re not there yet, but a little foresight can see that we may be going there!

While personal quantum computing is still a distant possibility, and might not ever be accessible to everyone, the development of AI in fintech could still allow the everyday investor to benefit. AI uses highly logical, rational, and super intelligent capabilities that are not weighed down by emotions like fear and anxiety. The potential for AI to greatly enhance the fintech space and improve financial management for people and institutions in the future is undeniable.

Artificial Intelligence As An Investment Tool

Trading algorithms, powered by AI, are already being developed and trained using historical data and proven successful strategies. Risk management techniques are also being built into machine learning, which will help safeguard against trading bots going haywire with people’s money. These algorithms, when combined with current and historical market data, can provide average investors with more accurate, up to date and profitable trading opportunities. By relying on the intelligence, stored data, and objectivity of trading bot algorithms, individuals and businesses can reduce the effects of emotional decision making, and make more efficient and effective trades. Investors can also spend time performing other productive activities instead of spending time researching market trends and trading on their own time — just let the bots take the wheel!

0 Percent is working actively in this space and has already developed several algorithmic trading bots! Take a look at one of its bots in action:

While algorithmic trading bots haven’t yet been perfected, they oftentimes outperform real human traders.

The use of AI in trading algorithms isn’t limited to individual investors. Financial institutions, large and small, as well as other major players across industries, are adopting these technologies to enhance their own trading processes and mitigate the risks associated with trading. By analyzing large amounts of data, AI can improve risk management strategies, and can better identify patterns that may not be noticeable to people. The adoption of AI in fintech has the potential to significantly improve the efficiency and profitability of trading, as well as minimize the negative impact of human error — although it should be noted that at least for now, it would be very unwise to rely exclusively on trading bots for all of your investing practices. The technology is still evolving.

AI in the Financial Sector

  • Trading algorithms: AI is currently being used by many industry leaders to develop algorithms that study & analyze market data, both current and historic, and make trades based on predetermined rules or patterns. These algorithms can be adapted & enhanced using machine learning techniques, potentially leading to more efficient and profitable trading outcomes.
  • Portfolio management: Because AI can be trained with current and historical market data, as well as proven successful trading strategies, the technology can be used to make investment recommendations, and make it easier for investors to execute decisions based on sound information.
  • Risk management: AI can be used to identify patterns & trends that might indicate potential risk and vulnerability, allowing investors to take proactive measures to mitigate and minimize those risks.
  • Fraud detection: AI can be used to analyze transactions and help identify anomalies that may indicate fraudulent activity. This could help reduce the risk of fraud in the crypto market, the overall financial sector, and a whole range of other industries and sectors. AI has the overall potential of reducing security risks for both individuals and large institutions.

AI & Crypto

The integration of AI in fintech has the potential to usher in many benefits to various sectors, including the notoriously volatile crypto market. AI powered trading algorithms and portfolio management tools can be used to study market data and make informed investment decisions based on data and not human emotion This can potentially help investors navigate the oftentimes unpredictable crypto market and make more profitable trades.

AI may also bring with it the potential to accelerate and optimize the crypto mining process, making it more efficient and profitable. Crypto mining is a notoriously energy intensive process, and any technological improvements in that space would be welcome by environmentalists and crypto miners alike.

Here are a few ways AI can enhance the crypto mining process:

  • Energy efficiency: Because AI can be used to streamline high-data processes, this can in turn reduce the energy consumption of the crypto mining process, thus reducing carbon emissions.
  • Hardware optimization: AI can potentially optimize the hardware configuration of crypto mining rigs, potentially improving performance & efficiency — reducing costs and increasing revenue.
  • Hash rate optimization: AI can be used to optimize the hash rate, or the measure of the processing power of a crypto mining rig. This would potentially increase the rate at which new units of cryptocurrency are created.

Successful Algorithmic Trading Book

Algorithmic Trading Accelerator

A Hybrid Approach

By utilizing AI in these ways, crypto mining operations can improve their efficiency, reduce costs, and increase profitability. The adoption of AI in the crypto mining process can significantly enhance the industry and bring numerous benefits.

While we are not yet at the point at which computers can totally manage out finances, it seems as though we are steadily approaching that reality. At the present time, these technologies are still developing and are largely still in the research and development phase. However, as bots are further trained and refined, it’s entirely possible that we may reach a point at which AI is responsible for entirely managing our investment portfolios. Until that time, many are opting in for a hybrid approach — combining the use of algorithmic trading bots with real human oversight and decision making.

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About the Author

Jeff Sekinger

Jeff Sekinger Founder & CEO, 0 Percent Who is Jeff Sekinger? Visionary Trailblazer Jeff Sekinger has been in the financial industry for over a decade. Starting out as a JP

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