Society and the financial sector are undergoing a revolution driven by technological advancements, being artificial intelligence (AI) and machine learningmachine learningkey elements. Applications and tools that would have previously been considered futuristic and works of science fiction are increasingly close to our daily lives, redefining the customer experience, asset management, the prevention of fraud and other crucial aspects of the area
The growing demand for automation and predictive analysis in finance is one of the most latent transformations. Processes that used to take days and required numerous people, currently can be done in seconds. A very simple example is the opening of a personal bank account. It is unimaginable for young people today to think that before it was necessary to wait in line for hours at the bank, wait for the manager to fill out various documents, take a ¾ photo and still have to return to the agency 15 days later to find out if the process was approved or not
In the same vein, the enhancement of customer experience is one of the use cases we feel the most in our daily lives, when we think about the integration of AI withmachine learning, be in thefront-end, with process automation, replacing manual tasks, improving customer service and implementing efficient chatbots, be in theback-end, by streamlining analyses such as loan granting and approval
Another highlight is the application of deep learning in credit risk assessment and management, as seen in the partnership between Citi and Feedzai. The use of Big Data andmachine learningin customer churn prediction and asset analysis also highlights the versatility of these technologies. Without the tools in the scene, business models such as online payments would be impossible, since transactions with the card are confirmed in seconds, with data navigating globally on an interconnected network with AI and ML to verify that a certain operation is being carried out by the cardholder
The transformation of the use of AI andmachine learningalso stands out in the stock market forecast, with the use of artificial neural networks and algorithms to estimate fluctuations and discrepancies. The implementation of these technologies in credit scoring, exemplified by Equifax, in the United States, highlights the scope on the agenda
Therefore, artificial intelligence and machine learning are fundamental catalysts in this entire scenario, providing efficiency, security andinsightspredictive analytics for the financial sector
In Brazil, The Central Bank is still paving a revolution with the BC# agenda, that involves Pix, Drex and Open Finance. Within this initiative, the use of AI and ML will be transformative for the country. The logic of the market will be inverted with the citizen ceasing to be a "customer" to become a "user", increasing competition among companies and service providers and, at the same time, diversifying opportunities for the consumer
