Open banking: novas possibilidades para o uso de machine learning nas fintechs brasileiras

• Ano de defesa: 2023
• Autor(a) principal: Nagli, Luiz Sergio Dutra
• Orientador(a): Albertin, Alberto Luiz
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Fintech; Open banking; Open finance; Machine learning; Regulação
• Palavras-chave em Inglês: Regulation
• Link de acesso: https://hdl.handle.net/10438/33244

The implementation of Open Banking was conceived and sponsored by the Central Bank of Brazil with the intention of fostering innovation, competition and the emergence of new products and services in the financial system. This initiative has the basic premise of returning data ownership to users, encouraging competition and new Business Models. Fintechs find in Open Banking an opportunity to have access to a complete and real-time position of their customers' financial life and find in Machine Learning new possibilities for products and services. By looking for patterns in large amounts of data, machine learning algorithms create new opportunities for fintechs. Thus, the general objective of this work is to identify the role of Machine Learning in the new Fintech Business Models to take advantage of Open Banking opportunities. For this, a qualitative research strategy based on a multiple case study was adopted, studying how Fintechs intend to explore opportunities for using Machine Learning. The results indicate new possibilities for using Machine Learning as an aggregation, prediction, recommendation and cross-selling tool in this new data environment supported by Open Banking, demonstrating how the analyzed companies made this implementation. The Fintechs analyzed have explored Open Banking opportunities with innovations in credit and also with the initiation of payments in context-based transactions, improving the customer journey in the most varied market applications.