Banca de DEFESA: Cristiane Ferreira Kovalski de Moura

Uma banca de DEFESA de DOUTORADO foi cadastrada pelo programa.
STUDENT : Cristiane Ferreira Kovalski de Moura
DATE: 18/12/2025
TIME: 12:30
LOCAL: https://meet.google.com/ort-amcn-iie
TITLE:

ALGORITHMIC RACISM IN CREDIT FOR BLACK BUSINESSES IN BRAZIL: A CONTEMPORARY ANALYSIS.

KEY WORDS:

Algorithmic racismo, Black-owned businesses, Credit assessment ou Credit evaluation, Access to credit.

PAGES: 171
BIG AREA: Ciências Sociais Aplicadas
AREA: Direito
SUMMARY:

This thesis investigates the effects of algorithmic racism on Black enterprises in Brazil, especially regarding access to credit, starting from the central problem: Given the increasing use of algorithms and automated systems in credit evaluation, how do these systems negatively impact Black enterprises in Brazil, hindering access to credit and perpetuating structural racism? This question guides the analysis of the dynamics of racial exclusion embedded in automated decision-making systems, in dialogue with current literature, including the contributions of Tarcízio Silva, Ruha Benjamin, Safiya Noble, Virginia Eubanks, and national research such as those developed by FGV. To address the problem, a theoretical research methodology was adopted, based on bibliographic review and critical analysis of books, scientific articles, and institutional reports. This approach made it possible to examine algorithmic racism as a contemporary form of structural racism, articulating it with the Brazilian reality of Black enterprises. The theoretical investigation also enabled the establishment of connections between financial institutions, law, and race relations, building an unprecedented intersection that reveals how automated credit scoring systems can reinforce historical inequalities.As a result, the thesis achieves a significant degree of originality, offering not only academic contributions but also practical inputs for public policies, regulatory strategies, and institutional actions aimed at democratizing credit and promoting racial justice. In conclusion, the thesis proposes political and regulatory strategies to confront algorithmic racism in Brazil, including algorithm transparency and auditability, public policies for financial inclusion, and the construction of fairer data models. The study highlights that combating algorithmic racism is essential to democratize credit and strengthen a plural and inclusive economic development.

COMMITTEE MEMBERS:
Presidente - 1647964 - VALCIR GASSEN
Interna - 1150035 - FERNANDA DE CARVALHO LAGE
Interna - 4878654 - LIVIA GIMENES DIAS DA FONSECA
Externo à Instituição - MARCOS VINÍCIUS LUSTOSA QUEIROZ - IDP
Externo à Instituição - Rafael de Deus Garcia - IDP