AI: A Pending Task for the Financial Industry, by Julián Colombo

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The financial sector invests more than US$65,000 million annually in technology. But the complexity of its legacy systems still holds back its innovation. Writes Julián Colombo, CEO and founder of N5.

In the technological landscape of the last year, the most debated topic was, without a doubt, the advancement and dissemination of Artificial Intelligence (AI) and Generative AI. And the figures from a recent Gartner study reinforce the interest that exists around the adoption of these technologies in the world: 92% of organizations plan to implement AI in their business by 2026, while 76% plan to implement Generative AI.

In the midst of this euphoria, the existence of such overwhelming figures should also lead us to wonder if we are not involved in a race that lacks a clearly defined finish line; especially in cases such as the financial industry. Each year, it invests more than $65 billion in technologies. But a lack of understanding of the challenge to be solved and the complexity of their legacy systems holds back innovation.

The implementation of AI has great potential, if it solves specific issues and transcends an isolated use. But it often concentrates on trivial aspects. Many industries, such as finance, still don’t understand its power and how to use it to boost business success.

The use of AI holds promise in financial areas such as data analysis, credit approval, information confidentiality, behavioral analysis, and customer satisfaction. It enhances decision-making, allowing huge amounts of data to be analysed in real time, identifying hidden patterns and improving the ability to predict a volatile market. At a generative level, it also allows the development of new services, facilitating innovation and adaptation to new demands, and feeding a widespread trend in the sector: hyper-personalization.

The AI revolution is shaping the path of transformation in the financial industry. But, for the investment to be successful, industry leaders will need to understand what the real problems are to be solved and where AI will have an impact.

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