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Governance For Credit Score Definition: Social Participation As An Instrument Of System Adequacy

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Detalhes bibliográficos
Resumo:The adoption of artificial intelligence systems to define the credit risk score has become an increasingly common situation. However, the adoption of such systems recommends the system to be suitable for the society where it will be used. In this way, the research reflects the importance of adopting multidisciplinary teams for the construction of artificial intelligence systems for credit analysis in order to provide such adequacy. The research problem refers to whether the adoption of professionals from diversified areas for the proper implementation of the artificial intelligence system for credit analysis, with a view to incorporating particularities of the local economy, will allow for a better adjustment of the risk assumed in each operation. The investigation to answer the problem focused on situations where risk analysis failed to capture particularities of local markets, generating inadequacy in risk analysis and exposing the financial institution to unwanted situations. As a conclusion of the research, it was observed that the implementation of artificial intelligence systems for credit analysis exposes the financial institution to new risks, deserving such situation an appropriate governance structure endowed with instruments that allow the adaptation of the model to the society that seeks to define the risk.
Autores principais:Barbosa de Souza , Maique
Assunto:Risco Análise de crédito Inteligência Artificial Risk Credit Analysis Artificial intelligence
Ano:2022
País:Portugal
Tipo de documento:artigo
Tipo de acesso:unknown
Instituição associada:Ponteditora
Idioma:português
Origem:e3 – Revista de Economia, Empresas e Empreendedores na CPLP
Descrição
Resumo:The adoption of artificial intelligence systems to define the credit risk score has become an increasingly common situation. However, the adoption of such systems recommends the system to be suitable for the society where it will be used. In this way, the research reflects the importance of adopting multidisciplinary teams for the construction of artificial intelligence systems for credit analysis in order to provide such adequacy. The research problem refers to whether the adoption of professionals from diversified areas for the proper implementation of the artificial intelligence system for credit analysis, with a view to incorporating particularities of the local economy, will allow for a better adjustment of the risk assumed in each operation. The investigation to answer the problem focused on situations where risk analysis failed to capture particularities of local markets, generating inadequacy in risk analysis and exposing the financial institution to unwanted situations. As a conclusion of the research, it was observed that the implementation of artificial intelligence systems for credit analysis exposes the financial institution to new risks, deserving such situation an appropriate governance structure endowed with instruments that allow the adaptation of the model to the society that seeks to define the risk.

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