The impact of AI on the cryptocurrencies market

By James Loft, Chief Operating Officer, Rainbird AI

The last decade has seen the global financial industry experience major disruptions courtesy of transformative technologies based in AI, machine learning and blockchain. Blockchain itself has given rise to cryptocurrencies, digital currencies based on encryption techniques used to regulate unit generation.

Innovation and disruption are reshaping the financial system on a daily basis, changing the way in which the world’s biggest firms conduct their business, and altering the way in which stocks, bonds and assets are traded.

The stock trade has a long-held obsession with automation technology. This shouldn’t come as much of a surprise given that automation brought about its modern incarnation.

It was toward the end of October 1986 when the traditional trading floor was replaced by the Stock Exchange Automated Quotation system (SEAQ). Known as the “Big Bang”, the introduction of a screen-based quotation system shortened the period between the initiation and execution of a trade, with brokers able to buy and sell stocks all over the world.

The death of the trading floor sent the market into overdrive. Before SEAQ, the average number of daily trades at the London Stock Exchange (LSE) was 20,000, with £700m worth of shares being swapped. After a few months that daily average had risen to 59,000. By 1987, automation saw the LSE turning over the combined value of the previous year’s trades in a month.

Throughout its history, the trading world has proven itself to be an advocate, and early adopter, of technologies that can be leveraged to gain a competitive advantage. And the next big revolution seems set to be powered by AI. Automated trading algorithms are entering the market, drawing investors on the promise of safe and steady returns.

For financial institutions such as brokerage firms and hedge fund investments, the application of AI to trading means a reduction in latency. By leveraging AI, firms can crunch numbers and analyse market data in real-time — at a faster rate and in greater quantities than ever before — and capture information that is beyond the scope of current statistical models.

As with any new technology, applications will be rolled out with caution. This is particularly true of the financial services industry, where technology has had a deep impact on the industry’s operations but has not been without its hiccups. Automation, while not at fault for the “flash crash” of 1987, contributed to the velocity of the fall in share prices.

Currently, the biggest appetite for AI trading is in pairing it with another industry disruptor: cryptocurrencies. The crypto market, with its lack of high barriers to entry and wide fluctuations in price, appears to be best suited to act as the basis for AI trading solutions.

With its steep price rises and sharp declines, the volatility of the cryptocurrency market provides traders with the potential to grow investment portfolios several times faster. But such is the speed at which the market turns, traders have been left disappointed by the performance of traditional market tools.

Being a speculative market, crypto provides a great training ground for AI and machine learning tools. And traders can definitely benefit from the technical analysis of historical quantitative data, given that AI and machine learning are perfect for assessing large data sets with high efficiency.

Earlier this year Rockwell Capital Management and TLDR Capital completed the first ever crypto trade brokered by AI. Using AiX, an intuitive AI trading platform, the cryptocurrency transaction was completed by an AI-powered chatbot. The deal represents a milestone for the financial services industry, and highlights how AI innovation is moving towards the foreground in the industry.
The broker executes trades by emulating human decision-making and natural language processing (NLP) which allows it to engage in thousands of conversations simultaneously, both with traders and systems alike. It communicates to establish the best price, enables bespoke bidding and provides information in real-time when market conditions fluctuate.

By utilising machine learning, it can discover the best and most relevant deals and, over time, will be able to anticipate decision-making. Given the heavy regulatory standards under which the financial services industry operates, the most innovative solutions are those which provide a detailed record of the data and the decisions that facilitate a trade.

But executing trades is just one facet of AI’s importance to the crypto market. As far as trading solutions are concerned, the hope is that machine learning and AI will help it grow and stabilise, as has been the case with traditional financial assets.