ISSN :2582-9793

Propensity Model using decision trees (LightGBM) for the Management of the Effective Credit Product in a Financial Entity.

Original Research (Published On: 09-Jan-2025 )
Propensity Model using decision trees (LightGBM) for the Management of the Effective Credit Product in a Financial Entity.

Norberto Ulises Roman Concha

Adv. Artif. Intell. Mach. Learn., 5 (1):3202-3215

Norberto Ulises Roman Concha : National University of San Marcos

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Article History: Received on: 16-Sep-24, Accepted on: 03-Jan-25, Published on: 09-Jan-25

Corresponding Author: Norberto Ulises Roman Concha

Email: nromanc@unmsm.edu.pe

Citation: Norberto Ulises Roman Concha, Andrea López, Kathy Ruiz-Carrasco, Carlos Chavez-Herrera, Dominga M. Cano, José Piedra, Juan Carlos Woolkut, Carlos Navarro. (2025). Propensity Model using decision trees (LightGBM) for the Management of the Effective Credit Product in a Financial Entity.. Adv. Artif. Intell. Mach. Learn., 5 (1 ):3202-3215


Abstract

    

The objective of this paper was to develop a propensity model based on decision trees (LightGbm) for the management of the Credit product in a financial institution. The CRIPS-DM methodology was used as a framework and Python/LightGBM was used for the development of the solution. As a result, it was possible to increase by 5% the effectiveness in credit for each month on a park of 200 thousand customers of the financial institution, which ensures the understanding of the applied model.

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