The use of artificial intelligence is currently paving the way to unprecedented possibilities in the financial sphere. With AI's growing capability and development, which is the current focus of most major market players, AI is carving itself an invaluable role.
With the use of machine learning, natural language processing, and deep learning, financial services are taking advantage of AI to maximize their efficiency, ultimately leading to bigger profits. AI proves to be a multi-faceted tool. Take brand intelligence and reputation management company Chatmeter as an example.
In April, they recently launched new features for their Natural Language Processing (NLP) sentiment analysis tool. Efficient sentiment analysis makes sense of large amounts of data to come up with expert takeaways. It helps companies make the most informed decisions when going forward and gives them a competitive edge.
AI can conduct sentiment analysis by looking at customer feedback, news headlines, and so on. This can help companies predict with more accuracy or attend to their customers' genuine needs with efficiency. In the case of Chatmeter, their new and updated AI tool helps them provide enhanced granular reporting and customization.
It will remain relevant to keep up-to-date on the latest news surrounding technology for the future to come. We live at the precipice of new technological dawns. For those seeking time for research, they might be thinking, "I need help to write my essay with best authors." In that case, they can use Studyfy and focus on what they want.
Moving along, Their NLP tool will help them extract more precise information from customer chatter that can help them make better insights. Additionally, they'll gain knowledge of specific elements that contribute to successful campaigns in their best-performing locations.
This is the power of AI. Its role in being able to extract profit-making insights from large-scale amounts of data at a corporate level gives companies an incentive to further solidify their role in their operations.
Market Surveillance At Its PeakAI has also made market surveillance execution much more efficient. While the term "market surveillance" can refer to a few definitions, in financial markets, it typically signifies the surveillance of fraudulent/illegal behavior, product ethicality, and if companies or institutions are following specific mandates.
AI is a necessity in market surveillance and imposing regulation. The sole fact that there is an unimaginable volume of data circulating in the digital sphere is the main reason for the further development of AI tools that help streamline market surveillance.
Recently, in 2019, Nasdaq, the globe's biggest stock exchange to date, released an AI tool designed for better market surveillance efforts. Nasdaq's tool, SMARTS, is currently used by more than 220 banks, brokers, and exchanges combined. It leverages the capabilities of deep learning and transfer learning technology to execute its tasks.
Enhanced PersonalizationWhile this fact may come off as counterintuitive, AI helps businesses offer better personalization for their customers, which improves deliverability by factoring in inclusivity and the like. Personalization not only potentially builds up customer trust, but it also helps customers navigate through tricky processes when dealing with a bank or a financial service.
In 2022, a good 18% of fintech investments were placed in personalization. For example, NVIDIA created Personetics, an AI solution for banking. It deals with and analyzes transaction data by using machine learning to provide more personalized advice to customers. Personalization, at the end of the day, helps businesses retain customers and boost loyalty through understanding their customers better.
Personetics is being used by many different fintech companies. A good note of its efficiency can be seen in the UK-based company Cleo. Through the use of Personitcs, they've reduced the need for customers to seek out customer service by 30%, enabling their customers to be more self-sufficient and have reportedly boosted customer satisfaction.
Powerful Assistance But FlawedAI has given way to the implementation of advanced tech into trading, with modern automation solutions like High-Frequency Trading (HFT) being used to analyze the market. HFT is made possible by the use of software that can analyze vast amounts of market data to execute trades at a speed that's impossible by human standards.
HFT has given leeway to modern-day traders who perform their day trades at unprecedented speeds. The role of AI in providing software that can do this should not be understated. AI algorithms can detect and identify patterns much faster than a human can, and they can detect and use trends that are not initially apparent to the human user.
As an example, substantial growth was observed in the Futures and Options volumes on the New York Stock Exchange (NSE) from the year 2020, which has consistently seen turnover increase up until now in 2023. High-frequency traders found unexpected profits because of COVID.
Since the beginning of COVID, there's been a clear increase in future and options turnover, and at present, the average daily turnover value is 10 times higher than before COVID started. The frenzy and growth happened because of many factors. A noteworthy factor was the explosion of amateur traders making easy money by trading options contracts.
The apparent attractiveness of using HFT software for trading should not overshadow the downsides of such technology. HFT algorithms react so rapidly to market signals and events that they cause a direct impact on asset prices. Unfortunately, this speed and efficiency can be the reason for sudden drops and spikes.
They generate volatility that can cause unpredictable glitches in the exchange. An example of this can be seen in May 2010. Stocks plummeted and were restored in just a few minutes, simultaneously deleting and restoring $1 trillion in market value. Volatile markets have become standard and the new norm since HFT programs were first released to the public.
Efficiency and profit continue to be prioritized, with stability taking the backseat since reportedly 70% of all trades in the US equity market were made by an HFT program. Leading figures argue that HFT poses a dangerous and systemic risk to the financial system amidst its growth and popularity.
How this will be regulated efficiently is still yet to be known, especially with big whales and institutional traders using HFT as well.