Artificial Intelligence reduces risk of non-payment

The prediction models carried out by Artificial Intelligence (AI), through the use of data, can reduce the risk of non-payment in credit. Tools such as big data and machine learning improve the ability to predict non-payment by 30% in the admission of new customers, according to a study by Experian.

This report highlights that 80% of financial institution managers are aware of the importance of using data and advanced analytics to generate business models with better results.

“Today there is a lot of overdue portfolio, after Covid-19, what we are looking for with different tools that analyze all this information, is to detect with algorithms and Artificial Intelligence, if a person is at risk or not. We see precisely this segmentation that helps us detect if someone is a possible debtor or is going to be one”, commented Rodrigo Garza, commercial director, of B12 Admark.

According to a survey conducted by the OpenText platform, 80% of financial organizations have contemplated the potential that AI tools represent for their businesses.

In addition, 52% of those consulted agreed that the prevention of fraud and the fight against money laundering will be the areas where this technology will have the most impact.

Automatic learning systems know the different behaviors of users, for example, if a word is repeated many times, there will come a time when the machine has already learned it. The same thing happens with behaviors such as biweekly payments, where perhaps paying the minimum on your credit card would qualify you as a person who could probably go into default,” Garza commented.

To extract value from big data, banks use algorithms to analyze a large set of information from a different source, from transactional databases, log files such as images, video or audio; Machine learning techniques help find patterns within the information provided and form prediction models, according to information from B12 Admark.

“Due to social networks, consumption behaviors are detected in a different way, a system, for example, will detect that a person possibly has a family, through the analysis of different sources of information, so it could offer a more appropriate product to their needs. profile,” Garza commented.

tool with potential


  • The millennial and Z generation are the ones that most demand digital banking channels.

New ways to win customers

  • Of financial institutions, 83% said that AI will create new ways to differentiate offers and win customers.

key in business

  • Of the financial companies, 80% highlighted that AI tools are key in their current businesses.

against fraud

  • Of those consulted, 52% agreed that the prevention of fraud and the fight against money laundering will be where this technology will have the most impact.

No physical visits

  • Of the young segment, 78% prefer not to visit a branch to carry out operations from applications.

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