Predicting mortgage default using convolutional neural networks

Publikasjonsdetaljer

Journal: Expert Systems With Applications, vol. 102, p. 207–217, 2018
Utgiver: Elsevier
Internasjonale standardnumre:
- Trykt: 0957-4174
- Elektronisk: 1873-6793
Lenker:
- ARKIV: http://hdl.handle.net/10852/71665
- FULLTEKST: http://publications.nr.no/1552287038/MortgageDefaultKvamme18.pdf
- DOI: doi.org/10.1016/j.eswa.2018.02.029

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.