How does Artificial Intelligence help in credit analysis?

In the credit granting process, it is essential to know the credit risk involved in making a loan to an entity or individual, so it is essential to analyze the client’s profile to have reliable information on their ability to pay and, obviously,  avoid delinquencies and non-payments.

However, the credit analysis must be carried out objectively, without prior biases, and it must cover the different financial data of the applicant in order to have the complete picture of their profile. This practice was done manually, which required several hours or days to complete the evaluation and then make an informed credit decision.

In this sense, AI helps to improve this process, carrying out the customer analysis quickly, without human biases and taking all the information from the SAT web service so that no financial or tax detail escapes.

In this way, it improves decision-making in the banking industry by offering a complete credit analysis with the plus of having a reduced cost compared to traditional credit risk methods, which also allows for a higher return on investment.

It must be considered that the algorithms with which AI works are very useful for processing an infinite number of structured and unstructured data without delay, which helps to identify some indications of credit risk in advance. This is possible due to the predictions made by the system with the database and the calculation of the variables to define a probable panorama in the future, in addition to the vision of the risk that exists in real and current time.

Likewise, with the AI applied to credit analysis, fraud problems can be prevented with the automatic learning of the algorithms that detect suspicious movements such as greater income from money laundering.

On the other hand, by automating the analysis tasks, the banking processes and services that applicants enjoy take less time, which generates a better experience for the client.