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Predicting mortgage default using convolutional neural networks - 2018

Author(s) Name:  H√•vardKvamme,Nikolai Sellereite,Kjersti Aas and Steffen Sjursen
Journal name:  Expert Systems with Applications
Conferrence name:  
Publisher name:  ELSEVIER
DOI:  10.1016/j.eswa.2018.02.029
Research Area:  Machine Learning
Abstract:

We predict mortgage default by applying convolutional neural networks to consumer transaction data. For each consumer we have the balances of the checking account, savings account, and the credit card, in addition to the daily number of transactions on the checking account, and amount transferred into the checking account. With no other information about each consumer we are able to achieve a ROC AUC of 0.918 for the networks, and 0.926 for the networks in combination with a random forests classifier.

Volume Information:  Volume 102, 15 July 2018, Pages 207-217
Journal Link:

https://www.sciencedirect.com/science/article/abs/pii/S0957417418301179