As it happens in so many other fields, AI is also gaining a lot of ground in the financial industry, where new applications and developments are found every day, for the benefit of both the activity of the institutions and the security of the customers.
In this sense, artificial intelligence can help companies in the financial sector to automate analyses related to processes such as risk management and fraud detection or prevention.
What is artificial intelligence?
AI is not as recent as you might think. In fact, some sources assure that it started in 1943, with an article by Warren McCullough and Walter Pitts, entitled A logical calculus of ideas immanent in nervous activity.
In it, a mathematical model was proposed for what we call neural networks today. Also mentioned in this history are the contributions of other great precursors of modern computing, such as Alan Turing.
However, there is no single definition of what AI is. Generally, this concept alludes to some qualities that are attributed to human intelligence, namely: the ability to perceive information, to process it, to analyze it and to act accordingly. In addition, other traits are added, such as flexibility, that is, being able to improvise or even do something new that was not foreseen.
At present, various developments, such as the OpenAI ChatGPT, allow to perform an easily, quickly, simply and efficiently variety of tasks, including text generation, translation, creating the code of a program, among others.
Uses of AI in the financial industry
In a particular way, AI has begun to be implemented in the financial industry, to automate various processes and improve the functioning of their platforms. We will know more details about it below.
Prevention of financial crimes
Some companies related to the sector, such as PayPal, are applying artificial intelligence for more efficient real-time analysis, to detect fraudulent transactions and comply with regulations related to money laundering.
It should be noted that international legislation on the subject requires financial institutions to contribute to the prevention of this type of crime and to report any suspicious activity. However, given the volume of operations, this must be done through programs that are capable of managing complex databases.
In the same way, AI has shown good performance in helping in the detection of possible credit card fraud, applying algorithms to analyze customer behavior, and detecting activity that contradicts the usual patterns in shopping habits, location, and other aspects.
Credit decision
Artificial intelligence is an alternative to help in decision-making when it comes to granting loans, both from the bank and from Fintechs, allowing a faster evaluation, at a lower cost.
Even, the subjective bias that may exist when such a task is entrusted to people is avoided, helping to better distinguish between high-risk and low-risk clients, even if they don’t have an excellent track record.
According to some sources, 40% of the companies that give business credit in the United States have improved their results thanks to this type of artificial intelligence tool.
Investment services
In addition to the above, another fertile ground for the application of AI in the financial industry is constituted by data-driven investments and prompts. Their performance has increased quite a lot in recent years.
In this regard, the investment algorithms allow to analyze the different stock markets, monitoring databases and news, which offers multiple benefits, by allowing more accurate decisions to be made when making transactions, increasing profitability.
Thus, an AI can make recommendations not only taking into account the behavior of the markets, but also the style of the investor and the goals he/she has set for him/herself. As a result, many institutions today entrust their various portfolios to an IA.
Risk management
The AI allows to significantly increase the speed with which the analyses are executed within risk management. Therefore, there are software providers that include AI-enabled improvements (machine learning and neural networks), increasing the efficiency of the models.
And taking into account that since the beginning of this year 2023 there has been a new set of rules of international application (Fundamental review of the trading book or FRTB), financial institutions will have to determine the risks associated with all their positions, which means a large volume of data. So, complex systems will be needed to analyze them, where AI, again, can help.
Payments and insurance claims
Insurance companies are not far behind when it comes to AI. They are already taking advantage of its possibilities to automate some processes; for example, applications, claims and payments, improving efficiency in this aspect.
Credit cards
Credit card issuers are doing the same: they can also analyze applications from potential customers, taking into account banking and demographic data, as well as consumer behavior, among others, allowing them to choose the product that best suits their profile.
Expectations, realities and risks
It is considered that the possibilities of AI in the financial industry or in other areas are still far from being fully developed. With its use, it is even expected to be able to make predictions for various businesses, as well as detect fraud. Although it should be clarified that, for stock markets, algorithms are tested with past information, which is no guarantee of future behavior.
However, not everyone involved in the sector has seen or been able to take advantage of these benefits. According to Forbes, while 93% of organizations consider that they can get something from AI, 40% of those who have made significant investments in this area still do not report profits, while 50% affirm that they have perceived the value.
On the other hand, some see more risk than opportunity. According to the same source, it is thought that up to 200,000 jobs could be lost in the US banking industry by 2030, due to AI.
For now, there is no doubt that AI is generating a lot of expectation in terms of new ways to gain profitability, making it a crucial component for many in their new business strategies for the future.