Bibliographic citations
Flores, E., La, D. (2022). Solución tecnológica que permita mejorar la experiencia y accesibilidad del cliente en el sistema financiero basada en el OpenBanking [Tesis, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/660714
Flores, E., La, D. Solución tecnológica que permita mejorar la experiencia y accesibilidad del cliente en el sistema financiero basada en el OpenBanking [Tesis]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2022. http://hdl.handle.net/10757/660714
@misc{renati/400155,
title = "Solución tecnológica que permita mejorar la experiencia y accesibilidad del cliente en el sistema financiero basada en el OpenBanking",
author = "La Torre López, Daniel",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2022"
}
The objective of this project is to propose a technological solution to improve the experience and accessibility of the client when applying for a loan in a financial institution. Through a Web Portal and/or Mobile Application, the client who wants to request a loan will be able to view, compare online credit alternatives that financial entities grant us and choose the offer that best suits him or her. The integrations that we will have with financial entities will be achieved by complying with international regulations and regulations such as PSD2 and international standards such as Open Banking, which promote innovation and competition, and it also favor the adaptation of banking services to new technologies. Depending on the loan amount requested by the client, the Fintech would finance the request, but if the amount exceeds what is allowed by the Fintech, the loan request is derived to the different financial entities subscribed to the Web Portal, generating competition mechanisms, improving the offer to the client, and promoting financial inclusion for both banked and unbanked people. The granting of credit to a client must go through a pre-evaluation process. This process uses a predictive risk model based on non-parametric data, which allows the evaluation of the client’s level of risk, the payment promise and the client's commitment to the loan.
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