THE USE OF ARTIFICIAL INTELLIGENCE IN ASSESSING A BANK CUSTOMER’S DEBT CAPACITY
2023, 101, No. 1
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Abstract
The purpose of this article is to discuss the issue of financial institutions, and especially banks, using artificial intelligence algorithms to assess the debt capacity of their potential borrowers. The author presents the view that the regulations currently in place are insufficient. In particular, there are no provisions in place to sufficiently protect the interests of bank customers. Additionally, the author considers what claims bank customers could have in the event that an algorithm made an incorrect assessment of their creditworthiness.
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Bibliography
Angwin J., Larson J., Mattu S., Kirchner L., Machine bias, ProPublica, hptts://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing (accessed 6 February 2023)
https://doi.org/10.1201/9781003278290-37
Bajor B., Article 69, (in:) Kociucki L., Kondek J. M., Królikowska K., Bajor B., Prawo bankowe. Komentarz do przepisów cywilnoprawnych, Warsaw 2020
Cichosz P., Systemy uczące się, Warszawa 2000
Fry H., Hello world. Jak być człowiekiem w epoce maszyn, Wydawnictwo Literackie 2019
https://doi.org/10.17104/9783406732201
Gudowski J., Art. 23 [dobra osobiste człowieka] (in:) Kodeks cywilny. Orzecznictwo. Piśmiennictwo. Tom I. Część ogólna, Warsaw, 2018
Karaszewski G., Article 415 (in:) Kodeks cywilny. Komentarz, Ciszewski J., Nazaruk P. (eds.), Warsaw, 2019
Kleinberg J., Lakkaraju H., Leskovec J., Ludwig J., Mullainathan S., Human Decisions and Machine Predictions, Cambridge, MA 2017, NBER Working Paper nr 23180, http://www.nber.org/papers/w23180 (accessed 6 February 2023)
https://doi.org/10.3386/w23180
Krizhevsky A., Sutskever I., Hinton G. E., ImageNet classification with deep convolutional neural networks, (in:) Advances in Neural Information Processing Systems 25, Pereira F., Burges C.J.C., Bottou L., Weinberger K.Q. (eds.), La Jolla, CA 2012
Michalak A., Charakter prawny ochrony tajemnicy przedsiębiorstwa (in:) Ochrona tajemnicy przedsiębiorstwa. Zagadnienia cywilnoprawne, Kraków, 2006
Wałachowska M., Rozdział V. Sztuczna inteligencja a zasady odpowiedzialności cywilnej (in:) Lai L., Świerczyński M. (eds.), Prawo sztucznej inteligencji, Warsaw, 2020
Wang D., Khosla A., Gargeya R., Irshad H., Beck A. H., Deep learning for identifying metastatic breast cancer, Cornell University Library, https://arxiv.org/abs/1606.05718 (accessed 6 February 2023)
Zieliński T., Obowiązek ujawnienia informacji na etapie przedkontraktowym odpowiedzialność z tytułu culpa in contrahendo - uwagi de lege lata i de lege ferenda, PPH 2016, 7th issue, Xiaoxiao L., Ant financial subsidiary starts offering individual credit scores, "Caixin", https://www.caixinglobal.com/2015-03-02/101012655.html (accessed 6 February 2023)
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