AI. These two letters are absolutely everywhere. It is almost impossible to open a web browser without being immediately directed toward a plethora of high-profile media featuring the latest AI initiatives from a wide range of business sectors.
By June this year, stock in hardware giant NVIDIA flew past the $135 mark, giving the company a market capitalisation of $3.34 trillion, overtaking Microsoft. Why is this interesting? NVIDIA staved off the obsolescence that other hardware companies suffered by maintaining its position as a graphics card stalwart for gamers and crypto miners, and subsequently going headlong into AI. A hardware company with a Magnificent 7-style market cap shows massive investor confidence in the use of AI within user experience.
The electronic trading industry is no exception. Development capital is pouring into AI initiatives and there have been a range of recent depictions by brokerage firms and technology providers with regard to how this can come to fruition.
Toward the end of July, retail CFD and social trading giant eToro released an AI-based advertisement for the forthcoming Olympic Games in Paris which will be shown on televised coverage for the duration of the event, with the cast of the video being AI-generated characters as eToro users.
eToro’s use of AI in the advertising campaign during the Olympic Games in Paris looks toward providing audio-visual insight to the investing public on how the company enables investors across the world to access global markets and connect with one another to grow their knowledge. Considering the online nature of the electronic trading industry, adding that ‘personal touch’ to the trading experience has long been a challenge. It is difficult to demonstrate the human connection between brokerage companies and traders due to the online nature and therefore perhaps one role of AI lies within marketing initiatives such as this.
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In Dubai in January this year, I debated the future of AI in trading alongside fellow electronic trading technology experts who agreed that AI has a place in the world of electronic trading, but that place may not be within any area of order execution. Rather, it would be a key advancement in natural language processing and the swift, rational arrangement of market-related content which can then be put in front of traders to help them make informed decisions.
If this can be considered a worthy viewpoint, AI has a future as an information enricher, rather than as a component within trading topography.
AI within front-end trading interfaces – Old cannot meet new
If AI has been such a significant attention-grabber in all areas of internet-related activity due to the supposition that it will be the next major advancement in technology, there must be a method by which it will eventually shape the interface between trader and broker.
Perhaps the development of AI toward how traders interact with their brokers may begin to be a catalyst that could begin to change the look and feel of trading platforms.
Many front-end platforms feature an obsolete graphical interface, there are a lot of also-rans, and condensing the chart-based, information-heavy front ends down toward the simplified mobile-oriented apps from neo banks and crypto exchanges has been a difficult task for the brokerage industry.
The more that AI becomes prevalent within the FinTech environment, hanging the way users interact with platforms. It will lead to many new developments, possibly each company will have its own vision of how it will be implemented. Some examples are where a platform vendor integrates AI into existing systems, whereas we build a new interface from scratch.
It is perhaps inevitable that AI will become increasingly prevalent within the FinTech environment, and in doing so it could transform the way users interact with retail trading platforms. This evolution is driving numerous new developments, with each company likely to have its own vision for AI implementation. Some platform vendors may have chosen to integrate AI into their existing systems to enhance functionality and user experience, while others may build entirely new interfaces from scratch.
These diverse approaches reflect the flexibility and potential of AI to revolutionize the trading landscape, offering personalized and efficient solutions tailored to the needs of modern traders.
The integration of AI into trading platforms is not just about enhancing current capabilities but also about redefining the user experience. By leveraging AI, companies can provide advanced data analysis, predictive insights, and automated trading strategies that were previously somewhat limited or offered via legacy third party solutions.
Generative AI pioneers such as Chat GPT or AI powered search engines such as Perplexity have begun to cause their users to adopt entirely new habits regarding reaching information. Now these generative AI services have to somehow be able to be used by traders in tandem with trading platforms, which presents a huge challenge and a deficit in the ability to keep up with the way traders find information via systems such as ChatGPT or Perplexity compared to how legacy trading platforms operate.
These generative AI solutions are relatively new but have taken the world by storm, so if it can be considered that many traders will be using these to aggregate and rationalize huge amounts of information from the internet, they would have to then try to process this information and execute it on a trading platform which is relatively unchanged in its format since the early 2000s which is the computer science world’s equivalent to the Paleolithic period.
Should the development of AI have to be used alongside legacy platforms, a degree of user unfriendliness would result, especially when considering the way younger people interact with the internet. It is more reasonable for firms to come up with new generation trading interfaces which include the right selection of new tools to suit these new habits.
It is therefore likely that AI-derived platforms, or platform interfaces which have been designed to work integrally with AI will not resemble the current architecture of the generic masses which feature similar characteristics such as candlestick charts and graphs and whose basic architecture dates back two decades, which in terms of software development is the dark ages.
If voice command systems such as Siri, itself a speech recognition AI, become combined with trading platforms that have been designed with AI in mind,, information could be delivered via voice prompts, meaning that mobile platforms and web platforms may well be of completely different designs to each other, and AI will influence their form and function in future.
There could also be an extension toward ancillary services which are used in the electronic trading industry. This summer, Erik Voorhees, a famous name for many years within the cryptocurrency world, founded a privacy-focused AI platform which uses blockchain for permissionless payment, as well as web3 infrastructure for local browser storage and end-to-end encryption.
This is another clear indicator that trading platforms will be very different to their existing form once AI becomes more mainstream, and electronic trading companies saddled with inflexible and outmoded platforms run the risk of being left behind.
Of particular note is that many companies in the cryptocurrency exchange sector are largely invested in the production of intuitive and simple apps which engage their customers, therefore initiatives from the cryptocurrency world are perhaps a sign of things to come in other sectors of the fintech and financial services industry.
New generation of tech for a new generation of traders
At TraderEvolution Global, we have looked closely at the dichotomy between the need to address fragmentation of market information whilst at the same time resolving the issue relating to incompatibility of ultra-modern generative AI solutions with generic, legacy trading platforms.
The TraderEvoluton AI Assistant is now available as a prototype, a pioneering development within the electronic trading industry of AI as a native feature within the front end trading interface.
The sheer volume and quality of content being produced today, coupled with advancements in technology, is paving the way for the emergence of a novel intermediary layer between consumers and the original sources of information and services.
The TraderEvolution AI Assistant was developed to filter, format, and compress information, delivering it to consumers in a personalized style and format.
Such rationalization of information is a significant boon to brokers wishing to provide quality services to retail traders of all levels of experience and adds important value to the user experience for the retention of existing traders whilst helping new traders learn the market in a less fragmented and easier-to-understand manner.
The importance of developing AI solutions in this vein has become a focal point of development within bridge providers recently too. As July drew to a close, Centroid Solutions unveiled a Beta release of a multi-lingual AI solution that is distributed to brokerages via the Centroid bridge, demonstrating that the remit of bridge providers extends further than liquidity connectivity and order flow management into the realms of content and information distribution.
Algos have trading automation covered, AI has content aggregation capabilities
Opinions appear to be quite well formed with regard to the use of AI within electronic trading at its current stage within a wide range of executives within a range of companies.
The consensus within discussions I have recently had on the subject of the role of AI within electronic trading has been quite uniform in that its current wave of development has its use case clearly defined within the content arena, be that market information for traders or the ability for brokerages to create a more engaging relationship with their customers as per the marketing angle taken by eToro.
The overall consensus however is that being able to provide market analysis and news aggregation which can be presented in an easy to understand form via generative AI integrated into platform front ends is an important step to take.
Lee Goldfarb at Edgewater Markets recently told me “I think that the way AI is marketed within the FX marketplace will be pivotal. Historically, the FX and CFD market has not always attracted the best market participants, and a lot of people get burned because of pseudo-courses, and most consumers don’t do very well. Educating customers is very important but it is equally important to see who is creating the material. We need to have well educated consumers understanding the risk they are taking, and AI content aggregation can be a way of showing people what happens with a leveraged trade and where it could go, if it is used in this way, it would be amazing for consumers as they would be able to make informed choices.”
This viewpoint is particularly poignant in that brokerages offering solely OTC products such as CFDs in a world in which regulators are insisting on the publication of warnings on their websites and marketing material relating to percentages of clients which make a loss, would be able to provide effective information to clients in order to increase their analytical skills toward more sophisticated and less risk-oriented asset classes.
AI as a method of honing traders skills
Being able to grow the skills of a trader who can be more confident during initial stages as a novice, and then move toward other product ranges via an AI assistant presenting easy-to-read information relating to various global markets is important.
During my many conversations with brokerage executives, the despondency which results from the practice of conducting client acquisition campaigns which attract novice traders that have small initial deposits and limited expertise is clear.
Spending thousands of dollars to acquire a client, only to then experience a small first time deposit which is then lost, is a negative experience for both broker and client, and has contributed toward the high percentage of losses within CFD traders being a regulatory moot point to the extent that in the United Kingdom, the average percentage of clients which make losses must be published on broker websites.
Being able to nurture client relationships via clear, effective information would be a great step toward remedying this matter. Traders can be shown where things are in the market. Thus, novice traders can then move forward from CFD trading toward other asset classes, growing themselves as a trader through content.
In this type of trading environment, AI may be able to point out and show different scenarios, perhaps historical events such as the worst 10 days in the market on a particular asset class, or ‘this is how much you can lose. Do you want to take up more correlated assets?” thus giving the tools and knowledge to be more responsible. Sitting down and working out a model like this is a lot of work, whereby an AI assistant can provide a quick snapshot.
In this case, perhaps CFD trading could be viewed as an entry-level product, and information provided by AI could empower traders to move up the asset class order without a long period of study as it presents them with information.
Overall, brokerages can view AI as more than a retention tool. It is far more valuable than that. Come and see us at the TraderEvolution Global booth at the forthcoming Finance Magnates Pacific Summit in Sydney, Australia, where you can see the new TraderEvolution AI Assistant in full detail.
I will also be engaging with fellow executives on the Centre Stage at that particular event, where ‘Technology and Asset Offering Beyond MT4’ will be the hot topic. Join us there on August 28 at 1400 AET!
