Brazil: Big data and automation help credit industry democratize access
RIO DE JANEIRO, BRAZIL – The financial system and the credit industry have been undergoing constant transformations, notably with respect to the analysis of credit concessions to borrowers.
With so many innovations in platforms such as Pix, Open Banking and Cadastro Positivo giving access to new customers and markets, it is expected that the data generated by these systems will enable the creation of new services and products, for instance.
In this context, granting credit transcends the analogical method of data verification, based on social capital: the main problem to be solved to reach a diagnosis is no longer investigating the past, but instead assessing the future of the borrower’s activity, through technologies based on big data and artificial intelligence (AI).
In the past, the information made available by government systems and agencies responsible for consumer borrower data has in fact always been very accurate. However, lacking consolidation, the time to collect, process, and even make this data available was tremendous.
Big data came to organize and consolidate the information in single platforms, allowing the lender to perform this same assessment in seconds, with only one CPF (Natural Persons Register) or CNPJ (National Registry of Legal Entities), for instance.
This modernization in the credit industry has created new opportunities for lenders, and has become a competitive agent. In other words, the faster and better the response, the better the credit. Nowadays it is possible to respond to limit analysis, concession and even make a PLD (Money Laundering Policy) with the support of big data systems.
It is possible to schedule queries in an extremely fast way, to mitigate analysis risks and even to program alerts for potential systemic issues or information inconsistency. These new techniques and the creation of methodology for research and data collection are contributing factors when it comes to the evolution of the credit industry.
All of this refinement and gains resulting from this system are a significant addition to the value of institutions’ businesses.
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This article was produced by The Rio Times’ automated newsroom system. How we use AI · Report an error · Editorial responsibility: Matthias Camenzind, Editor-in-Chief