PPGINF PÓS-GRADUAÇÃO EM ENGENHARIA DA INFORMAÇÃO FUNDAÇÃO UNIVERSIDADE FEDERAL DO ABC Teléfono/Ramal: No informado http://propg.ufabc.edu.br/ppginfo

Banca de DEFESA: LAION LIMA BOAVENTURA

Uma banca de DEFESA de DOUTORADO foi cadastrada pelo programa.
DISCENTE : LAION LIMA BOAVENTURA
Data: 06/02/2026
HORA: 14:00
LOCAL: Auditório 801 no 8º andar do Bloco B do Campus Santo André da Universidade Federal do ABC
TÍTULO:

Clustered Spearman Markowitz: A Feature Selection Method for Credit Scoring Model


PÁGINAS: 82
RESUMO:

Innovation in feature selection methods is essential for improving prediction systems adopted by financial institutions, especially in financial services involving credit risk analysis and the investment decisions necessary for loan approval. Careful feature selection not only enhances the performance of predictive models but also reduces potential financial costs associated with unnecessary data acquisition. In this context, this work presents the Clustered Spearman Markowitz (CSM), a novel method that combines Spearman rank correlation to group similar features, and Markowitz's asset allocation theory to determine the weights of these groups (clusters), interpreting the accuracy of the models generated by each cluster as return and their variance as risk. The Risk Return relationship associated with each group of features is then used to select only the features truly necessary for fitting the credit scoring model. The central goal of the CSM is to eliminate irrelevant or redundant features, contributing to more efficient credit scoring prediction models. The validity and the efficiency of the method were proven through extensive simulation tests and application to a widely used real dataset, as the Lending Club Loan Data. The performance of the CSM was compared to standard techniques and recent methodologies, demonstrating superiority in accuracy, F1 Score, and a significant reduction in the number of selected features, establishing itself as an important contribution to innovation in credit risk analysis and predictive modeling for financial institutions.


MEMBROS DA BANCA:
Presidente - Interno ao Programa - 2090028 - FILIPE IEDA FAZANARO
Membro Titular - Examinador(a) Externo ao Programa - 1763482 - GUILHERME DE OLIVEIRA LIMA CAGLIARI MARQUES
Membro Titular - Examinador(a) Externo ao Programa - 3044516 - LUNEQUE DEL RIO DE SOUZA E SILVA JUNIOR
Membro Titular - Examinador(a) Externo à Instituição - CRISTIAN JAVIER CANIU BARROS
Membro Titular - Examinador(a) Externo à Instituição - IVETTE RAYMUNDA LUNA HUAMANI
Membro Suplente - Examinador(a) Interno ao Programa - 1761105 - MURILO BELLEZONI LOIOLA
Membro Suplente - Examinador(a) Externo ao Programa - 1318146 - MAXIMILIANO BARBOSA DA SILVA
Membro Suplente - Examinador(a) Externo à Instituição - ANDRÉ LUIZ DELAI
Notícia cadastrada em: 09/12/2025 15:09
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