• Deep generative models for reject inference in credit scoring 

      Andrade Mancisidor, Rogelio; Kampffmeyer, Michael; Aas, Kjersti; Jenssen, Robert (Journal article; Peer reviewed, 2020)
      Credit scoring models based on accepted applications may be biased and their consequences can have a statistical and economic impact. Reject inference is the process of attempting to infer the creditworthiness status of ...
    • Explaining Predictive Models with Mixed Features Using Shapley Values and Conditional Inference Trees 

      Redelmeier, Annabelle Alice; Jullum, Martin; Aas, Kjersti (Chapter, 2002)
      It is becoming increasingly important to explain complex, black-box machine learning models. Although there is an expanding literature on this topic, Shapley values stand out as a sound method to explain predictions from ...
    • Learning latent representations of bank customers with the Variational Autoencoder 

      Andrade Mancisidor, Rogelio; Kampffmeyer, Michael; Aas, Kjersti; Jenssen, Robert (Journal article; Peer reviewed, 2020)
      Learning data representations that reflect the customers’ creditworthiness can improve marketing campaigns, customer relationship management, data and process management or the credit risk assessment in retail banks. In ...