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https://hdl.handle.net/20.500.11779/1912
Title: | Modeling Consumer Creditworthiness via Psychometric Scale and Machine Learning | Other Titles: | Muteri Krediverilebilirligini Psikometrik Olfek ve Yapay Ogrenme ile Modellemek | Authors: | Sahin Türkay Çakar Tuna Bozkan Tunahan Ertugrul Seyit Sayar Alperen |
Keywords: | Alternative data sources artificial learning creditworthiness factoring |
Publisher: | IEEE | Source: | Sahin, T., Cakar, T., Bozkan, T., Ertugrul, S., & Sayar, A. (2022). Modeling Consumer Creditworthiness via Psychometric Scale and Machine Learning. 2022 7th International Conference on Computer Science and Engineering (UBMK). https://doi.org/10.1109/ubmk55850.2022.9919596 | Abstract: | Although the predictive power of economic metrics to detect the creditworthiness of the customers is high, there is a rising interest in the integration of cognitive, psychological, behavioral, alternative, and demographic data into credit risk systems and processing the data through modern methods. The primary motivation for the rising interest is increased customer classification accuracy. In this research, customer creditworthiness was modeled through data consisting of personality, money attitudes, impulsivity, self-esteem, self-control, and material values and processed through artificial intelligence. The obtained findings have been evaluated as a reference point for the following research. © 2022 IEEE. | URI: | https://hdl.handle.net/20.500.11779/1912 https://doi.org/10.1109/UBMK55850.2022.9919596 |
ISBN: | 9781670000000 |
Appears in Collections: | Bilgisayar Mühendisliği Bölümü koleksiyonu Psikoloji Bölümü koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
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Modeling_Consumer_Creditworthiness_via_Psychometric_Scale_and_Machine_Learning.pdf | Full Text - Article | 883.54 kB | Adobe PDF | View/Open |
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