• Corpus ID: 238354372

Predicting Credit Risk for Unsecured Lending: A Machine Learning Approach

@article{Naik2021PredictingCR,
  title={Predicting Credit Risk for Unsecured Lending: A Machine Learning Approach},
  author={Kanchan Naik},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.02206}
}
  • K. Naik
  • Published 5 October 2021
  • Computer Science, Economics
  • ArXiv
Since the 1990s, there have been significant advances in the technology space and the e-Commerce area, leading to an exponential increase in demand for cashless payment solutions. This has led to increased demand for credit cards, bringing along with it the possibility of higher credit defaults and hence higher delinquency rates, over a period of time. The purpose of this research paper is to build a contemporary credit scoring model to forecast credit defaults for unsecured lending (credit… 

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References

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