Researcher: Merriam Thoka, University of Limpopo
Supervisor: Dr Hairong Bau, University of the Witwatersrand, Johannesburg
Tree-based machine learning (ML) models are non-linear predictive models utilized today due to their accuracy and efficiency, but understanding their decisions has received very little attention. Recently, banks are adopting ML to compute credit score because utilizing ML or AI in credit scoring is attentive to real-time signs of a potential borrower’s creditworthiness. The goal of the study is to create an interpretable credit scoring model that borrowers and banks can utilize to anticipate if a lendee will be able of paying back their debt, as well as to comprehend the logic behind the model’s prediction.
