Does AI-based credit scoring improve financial inclusion? Evidence from online payday lending

Hongchang Wang, Chunxiao Li, Bin Gu, Wei Min

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Artificial intelligence (AI) has become ubiquitous in the consumer finance industry. One of the major AI applications in this industry is AI-based credit scoring models. We investigate whether AI applications improve financial inclusion, as measured by three seemingly contradictory metrics, i.e. approval rate, default rate, and false rejection rate. We cooperate with an AI solution provider whose AI-based credit scoring models are widely used by online lenders in China. Using data obtained from these online lenders, we find that AI-based credit scoring models increase approval rate and reduce default rate simultaneously, which enhances both the magnitude and the quality of financial inclusion. AI-based credit scoring models also tend to reduce false rejection rate, suggesting that they can help provide access to capital to previously underserved population. We plan to collect more data and conduct additional analyses in the future to enrich our current findings and explore for underlying mechanisms.

Original languageEnglish (US)
Title of host publication40th International Conference on Information Systems, ICIS 2019
PublisherAssociation for Information Systems
ISBN (Electronic)9780996683197
StatePublished - 1984
Event40th International Conference on Information Systems, ICIS 2019 - Munich, Germany
Duration: Dec 15 2019Dec 18 2019

Publication series

Name40th International Conference on Information Systems, ICIS 2019

Conference

Conference40th International Conference on Information Systems, ICIS 2019
CountryGermany
CityMunich
Period12/15/1912/18/19

Keywords

  • Artificial intelligence
  • Credit scoring models
  • False rejection rate
  • Financial inclusion
  • Financial technologies

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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  • Cite this

    Wang, H., Li, C., Gu, B., & Min, W. (1984). Does AI-based credit scoring improve financial inclusion? Evidence from online payday lending. In 40th International Conference on Information Systems, ICIS 2019 (40th International Conference on Information Systems, ICIS 2019). Association for Information Systems.