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Explainable Loan Approval System


Ching Ng

05/05/2026

Supervised by Alexia Zoumpoulaki; Moderated by Bailin Deng

Using open datasets, develop an (online) application that allows you to load data and train a model that predicts loan approvals based on various input parameters, and more importantly, provides clear and understandable reasons for its decisions. The project will go beyond simple ml algorithms. Different areas of focus will be considered: e.g. interactive explainability, dataset augmentation, simplification, chatbots for explanations. Dataset identification, Model Development, Explainability, UI Development


Initial Plan (01/02/2026) [Zip Archive]

Final Report (05/05/2026) [Zip Archive]

Publication Form