2023-06-04 18:47:36
According to a report published by the IDB, the lending financial technology industry has seen an increase in recent years.
The report “Fintech in Latin America and the Caribbean: a consolidated ecosystem for recovery”published by the IDB in April 2022, revealed that the financial technology industry focused on online loans experienced a notable increase in recent years in Latin America.
This can be attributed to a synergy of elements such as the integration of financial technologies in the area, the increase in internet availability and the growing demand for fast and effective financing options.
This inclination originates from multiple variables, including the transformations generated by the pandemic, the bureaucratic limitations that prevent access to conventional credit by a considerable portion of the population, and the integration of technology in credit evaluation procedures. .
These elements exercised a significant influence and accelerated the adherence to said platforms in order to obtain financing.
In Argentina there are various factors that contribute to the limited availability of conventional loans.
“Regarding loans, the financial system has pending challenges in terms of people’s access, such as: incorporating more subjects, improving geographic coverage and reducing the gender gap in allocation,” said Fátima Maidana, Commercial Manager of Adelantos. com -leading company in online loans-.
According to the IDB, the financial technology industry focused on loans has grown in recent years in Latin America.
And he added: “Likewise, the adverse macroeconomic conditions in which the economy operated, as in the pandemic for example, and in particular the persistence of high interest rates in a context of contraction of activity, were reflected in the proportion of people with financing in an irregular situation”.
The increase in the number of users who lack access to traditional loans in Argentina is due to the unbanking of familiesin a context of strong economic recession and accelerated growth of inflation.
It is feasible for everyone to obtain information about their credit history, which can be consulted free of charge at the Central Debtors of the BCRA. To access this information, it is necessary to use the tax identification code.
The corresponding section of the Central Bank is responsible for collecting all the data required to generate a complete financial condition report. Each evaluated profile is assigned a rating on a scale of 1 to 6, based on its behavior over time.
Meaning of the score:
- normal risk. The payment of debts does not exceed 31 days from the due date.
- Low risk. Late payments up to 90 days from the due date.
- Medium risk. Delays in payments up to 180 days.
- High risk. Delays of up to one year in the payment of debts.
- Irrecoverable. Delays greater than one year.
- Unrecoverable due to technical disposition.
The lack of a strong credit history or a low score has led many people to face difficulties in accessing conventional loans, which prompts them to look for more inclusive options, such as digital loans.
The lack of traditional loans in Argentina is due to the unbanking of families in a context of strong economic recession and rising inflation.
These companies innovatively employ a variety of technologies to analyze the credit risk of individuals with limited access to banking services. By having these highly efficient tools, they can offer loans with more affordable conditions.
Methodology used by digital loan platforms
“When we receive a request, Adelantos.com’s technology is responsible for collecting traditional and non-traditional information from different data sources, and that information feeds predictive models trained with Machine Learning techniques that end up approving or rejecting the request,” Maidana said. .
And he added: “If approved, a proposal for a financial product is generated that fits the customer’s credit profile. The most important thing is that this happens automatically and instantly.”
Unlike banks, lending platforms use unconventional technologies and information sources to assess the capacity of each user.
The application of algorithms and machine learning models are efficient to analyze significant volumes of data and consider aspects such as income, expenses, work history and previous financial behavior.
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