The integration of artificial intelligence in finance has represented a revolution in the financial sector. The transformation that has been experienced in recent months has forever changed the way operations are executed. Furthermore, decision-making is now much simpler thanks to the data provided by these tools.
The digital transformation in financial services is already unstoppable, although not everything is so positive in this sector. In this sense, strategies must be created to mitigate risks in the implementation of AI in the financial sector. Aspects such as data protection, algorithmic bias or the risk of possible job losses worry many experts. In this article, we will address all these topics so that you know the risks and benefits of artificial intelligence in finance.
The most important benefits of integrating artificial intelligence in finance
Technological innovation in the financial field is the spearhead of digitalization, and both companies and clients can take advantage of many of the advantages that artificial intelligence provides in the financial sector. Next, we are going to review the most relevant ones.
Automation of financial processes with AI
Many routine tasks no longer require human presence to carry them out. This has been present in the sector for several years, but with the implementation of artificial intelligence in finance it has gone one step further.
Now the automation of more complex financial processes with AI, the management of investment portfolios or the analysis of financial data with artificial intelligence can also be achieved. The digital transformation in financial services favours the development of applications such as the well-known robo-advisors. These systems are used in some banking entities to invest automatically on behalf of clients who have little knowledge of the subject. In this way, the risks of purchasing undesirable assets are minimized.
All this allows employees of companies in the sector to dedicate their time to strategic tasks with greater added value.
Data-Driven approach
Decision-making is one of the most important aspects of any business since the success or failure of the company depends on it. Until now, many of these strategies were adopted based on the advice of experts or in consensus with other managers. However, this led to many errors, since humans are not always able to take into account all the variables to make the final decision.
Artificial intelligence in the financial sector has great analytical capacity. This is possible because the tools are hosted on servers with high performance and very high processing speed. Furthermore, the complex algorithms used by virtual reality applications are capable of identifying patterns, trends and even risks.
Analyzing financial data with artificial intelligence forms a much stronger basis for making data-driven decisions. Of all the risks and benefits of artificial intelligence in finance, this is one of the most relevant.
Bank fraud prevention
The great ability to analyze enormous amounts of information also makes it possible to fight fraud. Each transaction is examined in real-time and artificial intelligence in the financial sector assesses the risk level of all of them. It does this by taking into account previous transfer patterns of the accounts involved or by possible account anomalies.
So, for example, thanks to data analysis with artificial intelligence, if a client suddenly starts strangely issuing transfers to another country, the AI acts before cybercriminals steal the money accumulated in the user’s global position. Technological innovation in the financial field is responsible for preventing numerous crimes.
However, technology is not perfect, so there is always a department in charge of supervising all this activity. Of course, until its implementation in the sector, it was necessary to analyze all transactions manually one by one. Today, improving operational efficiency in finance thanks to AI is a reality.
Personalization of the experience
Each client is unique and the financial services they may need are also unique. In this sense, collecting your data can be very useful in understanding your tastes, interests or even your purchasing behaviour. Thanks to all this information, artificial intelligence is capable of creating a commercial profile based solely on your preferences. Its machine learning algorithms leverage this information to provide each customer with unique offers tailored to what they may demand in the future.
In addition, by knowing other data from your history, the company can develop a risk profile of each user to offer financial products without the need for any request to be made. For example, in the case of pre-granted personal loans, the money will be in the user’s account in a few clicks and without waiting.
Virtual assistants
Another field in which digital transformation in financial services stands out from any other alternative has to do with solutions aimed at improving customer service. More and more companies are using chatbots to serve their users.
Its operation is very simple. Customers ask questions to the chat just as they would with a human manager, and it tries to answer them based on how it has been programmed. The simplest ones have a small script that they explain naturally. If the question that has been asked has no possible answer, they transfer the chat to a human.
Technological innovation in the financial field is also responsible for other more advanced chatbots capable of using natural language that is difficult to distinguish from that of a person. These are the ones with the most possibilities since they even allow small operations to be carried out.
Virtual assistants, in all their variants, are one of the most interesting applications of this emerging technology.
The most important risks of the integration of artificial intelligence in the financial sector
The European Union has already laid the legal foundations for artificial intelligence with the first European directive that regulates its development. However, there are still many issues that concern users and also companies, so the risks and benefits of artificial intelligence in finance must be taken very seriously before its definitive integration. To avoid problems, strategies must be developed to mitigate risks in the implementation of AI in the financial sector.
Privacy and information security
Artificial intelligence in finance compares millions of financial transactions every day, which can become a very serious problem if a security breach occurs. Cybercriminals could take advantage of the qualities of these tools to steal large amounts of confidential data.
On the other hand, if algorithms were manipulated without drawing the attention of corporate security teams, the consequences could be dire. AI’s ability to execute transactions autonomously could compromise the accounts of millions of customers.
However, companies invest a large amount of resources every year in making their servers increasingly more secure. Additionally, two-step authentication processes make security breaches very difficult. And we must not forget that behind artificial intelligence there are teams of numerous developers ensuring the correct functioning of computer systems. Without these protective measures, digital transformation in financial services would be much more difficult.
Algorithmic bias
Technological innovation in the financial field is also dangerous. The developers of artificial intelligence in finance, as if they were parents, can unconsciously incorporate biases that in the long term produce erratic functioning of these tools. This is one of the biggest fears of experts, but it is possible to avoid it, especially during the initial phases of development, which are the most delicate.
The problem with algorithmic bias is that it can cause artificial intelligence to make decisions that are discriminatory or harmful to some customers, something especially dangerous when automating financial processes with AI. Thus, while some would benefit, others would suffer the consequences. Let’s show you an example.
Self-driving cars have already suffered this popular scrutiny. The developers of a self-driving vehicle, who are they going to prioritize, its driver or a baby found in the middle of the road? Morally, the baby would always be the beneficiary, and many drivers would swerve to avoid it. Now, a computer program will act according to its coding and, if it must protect the occupants, it will have no problem running over a newborn.
Taking the issue back to the financial sector, it could happen that a group of investors with more resources would benefit from AI decisions. And they might think that, by having more assets, they will leave more benefits for the financial institution. On the contrary, it could propose worse investments to those with less money.
Therefore, it will be necessary to thoroughly review each line of code to prevent these types of problems from happening during digital transformation in financial services.
Job losses
This is a real fear, since the greater productivity of artificial intelligence tools in the financial sector can lead companies to make that decision, something that has already been seen in the analysis of financial data with artificial intelligence and that is not within the reach of any human team. Routine tasks that were previously performed by people now no longer require their presence. This, above all, is affecting labour groups with less training.
However, employment growth among application development professionals and in higher training segments is a reality at the moment. Banks like BBVA have increased their workforce by 3% in 2023 alone. CaixaBank has also grown by 2% in the number of employees, and the general situation of the sector is positive. Of course, it is essential to direct the unemployed towards training programs that have a place in the new financial reality. If not, they may find it difficult to relocate.
Operational risks associated with AI
Last November 2023, millions of Spaniards saw how their cards did not work. They also could not make transfers through Bizum or buy online. The Redsys platform suffered a computer problem that made any operation impossible for several hours, creating real chaos. Technological dependence entails these types of problems, and they could be enhanced with the massive integration of artificial intelligence.
Errors in an update that corrupts the code or crashes a server are real dangers that must be taken into account. To minimize risk, companies have support servers and isolated and secure systems where tests are carried out before releasing any code update. In any case, it is very important to pay attention to this aspect.
The reception of artificial intelligence in finance is very positive. After knowing all the risks and benefits of artificial intelligence in finance, you can now understand why more and more companies are opting for its integration to a greater or lesser extent.
The automation of financial processes with AI is already present in the sector, and many companies have understood its importance in reducing costs and seeing their profits grow. Strategies should only be developed to mitigate risks in the implementation of AI in the financial sector.
