Joint research unit 7235

Scaling up SME’s credit scoring scope with LightGBM

Bastien Lextrait

Small and Medium Size Enterprises (SMEs) are critical actors in the fabric of the economy. Their growth is often limited by the difficulty in obtaining financing. Basel II accords enforced the obligation for banks to estimate the probability of default of their obligors. Currently used models are limited by the simplicity of their architecture and the available data. State of the art machine learning models are not widely used because they are often considered as black boxes that cannot be easily explained or interpreted. We propose a methodology to combine high predictive power and powerful explainability using various Gradient Boosting Decision Trees (GBDT) implementations such as the LightGBM algorithm and SHapley Additive exPlanation (SHAP) values as post-prediction explanation model. SHAP values are among the most recent methods quantifying with consistency the impact of each input feature over the credit score. This model is developed and tested using a nation-wide sample of French companies, with a highly unbalanced positive event ratio. The performances of GBDT models are compared with traditional credit scoring algorithms such as Support Vector Machine (SVM) and Logistic Regression. LightGBM provides the best performances over the test sample, while being fast to train and economically sound. Results obtained from SHAP values analysis are consistent with previous socio-economic studies, in that they can pinpoint known influent economical factors among hundreds of other features. Providing such a level of explainability to complex models may convince regulators to accept their use in automated credit scoring, which could ultimately benefit both borrowers and lenders.

AGENDA

Monday 4 March 2024

The Bright Side of the GDPR: Welfare-improving Privacy Management

Shiva Shekhar (Tilburg Univ)

The Bright Side of the GDPR: Welfare-improving Privacy Management

Monday 4 March 2024

Law, Institutions and Economics in Nanterre (LIEN)

Shiva Shekhar (Tilburg Univ)

The Bright Side of the GDPR: Welfare-improving Privacy Management

Tuesday 5 March 2024

Recherche et Economie et Socioéconomie Politique, des Institutions et des Régulations (RESPIR)

Thomas Angeletti (Université Paris Dauphine PSL & IRISSO CNRS)

L’invention de l’économie française

Tuesday 5 March 2024

L’invention de l’économie française

Thomas Angeletti (Université Paris Dauphine PSL & IRISSO CNRS)

L’invention de l’économie française

Tuesday 5 March 2024

Webinar TELE – Theoretical European Law & Economics

Ester Manna (University of Barcelona, Spain)

3:00 pm to 4:15 pm (Paris time)

TBA

Tuesday 5 March 2024

TBA

Ester Manna (University of Barcelona, Spain)

3:00 pm to 4:15 pm (Paris time)

TBA

Wednesday 6 March 2024

Économies du monde musulman

Amal Briki (Agence Alnaft, Alger)

Les déterminants de la performance bancaire en Algérie

Wednesday 6 March 2024

Les déterminants de la performance bancaire en Algérie

Amal Briki (Agence Alnaft, Alger)

Les déterminants de la performance bancaire en Algérie

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