Not only has the fintech phenomenon translated into a highly lucrative market in the digital age, but it also has scope to grow exponentially in the years to come.
To this end, the fintech marketplace was estimated to be worth $133.84 billion at the end of 2022, while total revenues are expected to peak at $556.58 billion in seven years’ time.
This means that the global fintech space will grow at a CAGR of 19.5% between now and 2030, as the underlying technology continues to evolve and the market unearths brand new applications.
This will continue to improve higher levels of financial inclusion, both regionally and at national level. In this article, I’ll focus on how fintech is aiding stock market trading and making this more accessible to aspiring investors, while asking how the trend has evolved over time.
The Democratising Impact of Fintech
Historically, stock market trading was the preserve of corporate investors and big bankers, who tended to monopolise the type of datasets required to make informed decisions.
More specifically, they controlled access to this information and the means of analysing it in detail and in real-time, affording them a critical advantage when it came to minimising risk and optimising profitability.
For aspiring retail traders to muscle in on the action and engage in relatively simple actions such as buying Microsoft stocks, they would have had to previously subscribe to a stock research firm to access the necessary data and make informed decisions. They also had the option of paying stockbrokers a premium for specific datasets, of course, but both practices were incredibly costly and capable of eating significantly into any potential profits.
There’s no doubt that the advent of fintech has challenged this status quo, establishing it as a disruptive and ultimately democratising technology.
It has achieved this by bringing advanced data analytics to the masses, largely through reputable trading platforms that typically feature a huge range of technical indicators and insights. This range even includes innovative, rule-based investment engines and algorithms, which are capable of analysing more than one billion data points simultaneously.
Unlocking Automated and High Frequency Trading
The proliferation of algorithmic trading has also changed the stock trading landscape, by enabling you to execute automated trades and a high volume of orders simultaneously.
By accessing algorithmic trading tools and advanced charts (which help with the creation and definition of the criteria that you use to program your algorithms), it’s possible to generate a largely passive income stream from stocks without overly increasing your market exposure or level of risk.
This also unlocks a larger selection of trading strategies, particularly ‘scalping’ and ‘day trading’. Both strategies are synonymous with forex and stocks, while they enable traders to speculate on price movements and secure incremental profits without having to assume ownership of the underlying financial instrument.
These strategies share a number of inherent similarities, but while both require traders to ensure that no positions remain open overnight, scalping executes a larger volume of orders during each 24-hour period and may often close positions after just a few minutes.
But why is having access to such strategies important? Well, they afford you flexibility in terms of how you trade and tackle the stock market’s innate volatility, rather than forcing you to rely solely on long-term, buy-and-hold strategies that put you at the mercy of medium and long-term price shifts.
With scalping and day trading, you can attempt to leverage the stock market’s volatility to your advantage, while utilising algorithmic and automated tools to optimise volumes and profitability in a scalable way.
The Last Word – The Role of Artificial Intelligence (AI)
Fintech innovation has also been built on principles such as big data and machine learning, the latter of which is a driving principle of artificial intelligence (AI).
These concepts are central to the collation and real-time analysis of huge swathes of data in the digital age, with some AI systems even able to identify trends in vast but unstructured information resources such as social media.
As a result, AI is playing an increasingly pivotal role in improving predictive analytics, which is the process of using data to forecast future events and outcomes. This, in turn, describes the undertaking that investors perform every time they place a trade, especially speculative traders who look to derive short-term profits through incremental price shifts.
So, by accessing more advanced (and informed) statistical models that draw data from a large array of sources, it’s possible to predict future price movements with far greater accuracy and improve profitability as a result.
As you can see, the burgeoning fintech space continues to have a significant impact on the financial markets, both in terms of their accessibility and how you’re able to manage volatility in the pursuit of profits. This trend shows no sign of abating any time soon, while there’s no doubt that the continued evolution of AI will have an even greater influence in the years ahead!
