As we have seen in previous posts, artificial intelligence has already come a long way since its beginnings, positioning itself as a key element in different fields and sectors and becoming a fact in many aspects of our lives. Today we will see how artificial intelligence is used in one of its most interesting applications.

In the vast majority of case studies on the use of artificial intelligence, the basis of the technology has to do with the use of data and how companies can make efficient use of it. This is where artificial intelligence and machine learning come into play, either to process and analyze a large amount of data or to work with a smaller universe of data in the case of reinforcement learning.

Reinforcement learning allows artificial intelligence technology to require a smaller amount of data than, for example, big data, since it uses pattern learning on the data, without being guided by a human who has previously analyzed the data.

Potential for use in Fintech

Traditionally in the banking and fintech sector, personal relationships with customers have been the basis for decision making. In the digital world in which we live, these personal relationships are increasingly diluted, and that is where AI can be used, on many occasions, to recover that relationship in a different customer profile than the traditional one, using data and information that can be compared and result in services or products that the customer needs. 

Artificial intelligence in decision making

Reinforcement learning has a major impact on management decision making. This is where data analytics delivers results focused on the requirements of both asset diversification and investment styles.


Roboadvisors are used by users to make financial decisions, both in investment funds and asset portfolios. In this area, artificial intelligence can take into account data from quotes, bonds, investment funds, etc... and can help make recommendations on when to buy or sell. These systems are increasingly used in financial companies or startups with financial technology.

Fintech business process

Predictive analysis of users and the use of financial services can directly affect commercial strategy, both in sales management and customer acquisition, as well as in the optimization of resources. In this way, it allows you to update your customer acquisition or management strategies, adapting them to the needs of your customers.

Retail customer management

Artificial intelligence services focused on portfolio management in different market segments allow retail clients to access management or advisory services that were previously reserved for high net worth and more traditional private banking clients. 

This is also achieved by using machine learning, which allows, on the one hand, the analysis of different assets differentiating by risk profiles and significantly reducing the costs involved.

Artificial Intelligence in banks.

The application of artificial intelligence in banks currently focuses mainly on three points. The first is the use of chatbots for customer service through the bank's own websites, with the aim of solving customer problems in real time. The second is fraud detection, using algorithms that protect both customers and the bank in the early detection of these cases. The third is credit applications in which the underwriting and decision-making process is automated for the customer.

Author: Juan EsteveDirector of the Training Department at