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Explainable artificial intelligence for digital finance and consumption upgrading

Author

Listed:
  • Zhou, Linjiang
  • Shi, Xiaochuan
  • Bao, Yaxiong
  • Gao, Lihua
  • Ma, Chao

Abstract

Recently, the role of digital finance in promoting consumer upgrades has become increasingly evident. By applying boosting trees and Shapley values, we proposed an explainable artificial intelligence method to obtain more effective analysis results than those obtained using linear regression models.

Suggested Citation

  • Zhou, Linjiang & Shi, Xiaochuan & Bao, Yaxiong & Gao, Lihua & Ma, Chao, 2023. "Explainable artificial intelligence for digital finance and consumption upgrading," Finance Research Letters, Elsevier, vol. 58(PC).
    • Handle: RePEc:eee:finlet:v:58:y:2023:i:pc:s1544612323008619
    DOI: 10.1016/j.frl.2023.104489
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    References listed on IDEAS

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    7. Wu, Zixi & Wang, Yiqin, 2023. "Consumer finance and consumption upgrading: An empirical study of CHFS," Finance Research Letters, Elsevier, vol. 54(C).
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    Full references (including those not matched with items on IDEAS)

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