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How AI is revolutionising finance

May 29, 2024

Artificial intelligence (AI) has become one of the biggest revolutions in recent years, and tools that make use of it are becoming increasingly popular on the internet. Without going any further, ChatGPT, a language model developed by OpenAI, has been the fastest platform to reach 100 million active users in the history of the internet, far surpassing Facebook, Instagram or TikTok.

Its applications are infinite, but if there is one field where AI still has a long way to go, it is none other than finance. Below, we will look at the main applications of AI within the financial industry and how it can revolutionise this important area of our daily lives.

What is Artificial Intelligence?

Artificial intelligence (AI) is a branch of computer science that simulates various aspects of human intelligence, such as learning, perception, reasoning and decision-making. AI is based on the use of algorithms and mathematical models that allow systems to learn from data and improve their performance over time.

Although its first historical references date back to the 1930s, when Alan Turing designed his famous "Turing machine", it is only now that it has acquired great popularity, thanks to the proliferation of open applications that make use of it and, above all, to the fact that its use has become public and free of charge.

AI has undoubtedly proven useful in a wide range of applications, from healthcare and manufacturing to logistics, commerce and, of course, finance. And, over time, artificial intelligence is expected to have an even greater impact on the way we work, communicate and engage with the world around us.

Applications where AI can revolutionise finance

The financial sector is undergoing an unprecedented digital transformation. Physical bank branches have given way to the use of digital applications through fintechs, and open banking has developed standards to open up the financial infrastructure to third parties. As a result, this financial innovation has succeeded in improving the user experience and extending financial education to counties with a low banking adoption. 

All of this has been made possible in part by the application of artificial intelligence within their financial processes. And although the applications of AI are almost infinite, there are some fields where this technology is particularly interesting, especially when it comes to improving processes or creating new ones. All of this to improve client experience and reduce operational costs for intermediaries. 

Financial fraud prevention

The ability of AI to detect and prevent financial fraud is one of its main added values. In particular, AI is able to filter through large amounts of financial data in real time in order to find patterns that may indicate fraud, such as transactions carried out in unusual geographical locations or through accounts that have never been used before.

But that’s not the end of it, because fraud-enhancing technologies are moving faster than modern anti-fraud systems can keep up with. AI can learn and adapt to new fraud patterns as they emerge. The automatic learning algorithms can be trained on historical fraud data and then applied in real time to detect suspicious transactions. 

Reduce security risks

As with fraud, AI is capable of identifying and correcting some security breaches on a massive scale automatically. Also, and given that the dangers on the internet are the order of the day, AI can be trained to update itself in the face of new threats.

Some of the applications of AI in this field are the detection of abnormal patterns in a dataset, the analysis of server security logs, the analysis of phishing emails or the detection of common patterns in messages or senders. 

Better knowledge of customers

AI, together with data and big data analysis tools, allows you to analyse vast amounts of information about your customers, including their transactions and online financial activity. 

However, AI doesn’t just feed on users’ financial information. It can also analyse the comments of customer feedback on social media and other platforms to better understand their needs and preferences. This allows companies to adapt their products and services to satisfy the specific needs of customers.

Process automation

By understanding natural language, AI is able to read and comprehend texts written by humans, such as emails, reports, and documents, and even attend meetings to synthesise all the information or take minutes. Additionally, AI can analyse and understand images and videos, enabling automated systems to perform tasks such as object detection and recognition, motion tracking, and barcode reading.

As AI continues to transform various sectors, its impact on the finance and treasury field is particularly significant. AI makes it possible to automate repetitive and tedious tasks, like accounting and bank reconciliation by finance teams, tasks that until now required human intervention.

24/7 client attention

Artificial intelligence also makes it possible to provide personalised customer service to customers of financial intermediaries, 24 hours a day, 7 days a week. This is made possible by tools such as chatbots, which can interact with customers more effectively, using machine learning to improve their ability to answer questions and understand customer needs.

While chatbots are a common application in many large banks and companies, their latest big breakthrough is ChatGPT, a programme that synthesises natural language and responds as if there were a person behind the conversation. In addition, it applies a deep learning technique called Transformers to generate more accurate and coherent responses. Thus, rather than talking to a machine, the customer has the feeling of being attended to by a human, which increases their satisfaction.

Improving credit decisions

One of the most complex activities of any financial intermediation company is trying to ascertain the creditworthiness of a person in order to grant a bank loan. In fact, on many occasions, this process can lead to numerous losses if it is not carried out correctly. And, in any case, it is a lengthy process that does not always end in the best way, neither for the debtor nor for the creditor.

By analysing large amounts of applicant data in real time, AI can make accurate predictions about the applicant's ability to pay and credit risk - easily and, above all, quickly. In addition, it can personalise credit offers based on the individual needs and preferences of applicants, improving the customer experience and increasing approval rates.

Improving investment services

In recent years, some investment services directly carried out by robots, such as automated investment managers, better known as robo advisors, have become very popular. These are sort of digital investment managers that use algorithms and technology to provide investment recommendations to clients. But for the moment, they use basic instruments, such as index funds or ETFs, to compose an investment portfolio tailored to each client's risk profile.

Artificial intelligence aims to go one step further, as they try to replace, or at least complement, the human effect and the talent of the best investment managers. And although it may sound utopian, information is becoming increasingly abundant, making it possible to better train these digital managers.

Improved insurance underwriting

Another field where artificial intelligence has a multitude of practical applications is the insurance industry. On the one hand, because it facilitates the management and identification of policyholder risks, as in any other financial field. But, above all, because it increases efficiency and speed in the identification of claims, detecting possible fraud and improving the relationship with insurers.

Cost reduction

The digitisation of processes has enabled companies to significantly reduce costs, and artificial intelligence is a great ally in achieving this. Ultimately, it is the logical consequence of all the applications that AI has on the financial industry.

But AI is not a mere substitute for human resources. In fact, thanks to its potential, its technology complements the human contact centre when properly integrated. After all, the goal of any business is to make as much profit as possible, and the financial industry is no exception.

Conclusions

Ultimately, as you can see, AI is revolutionising finance in a number of ways, from data analytics to fraud detection, process automation and risk management.

As a result, investors and companies can make more informed and efficient decisions, allowing them to maximise returns and minimise risks. In the coming years, AI is sure to continue to transform finance and companies that adopt this technology will be better positioned to compete in an increasingly demanding and dynamic marketplace.

Tomas
Gil
CTO @ Embat
Tomás, with a background in telecommunications engineering, began his career in bank connectivity when he took on the role of CTO at Fintonic Latam, before joining Embat.

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