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Lending by Algorithm: Fair or Flawed? An Information-Theoretic View of Credit Decision Pipelines
15 references·0 citing·47 second hop
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References

  • 2021Capability, opportunity, and motivation: an across contexts empirical examination of the COM-B model249 cited
  • 2024How do machine learning and non-traditional data affect credit scoring? New evidence from a Chinese fintech firm135 cited
  • 2024Data governance & quality management—Innovation and breakthroughs across different fields128 cited
  • 2023Algorithmic discrimination in the credit domain: what do we know about it?99 cited
  • 2024Prediction of bank credit worthiness through credit risk analysis: an explainable machine learning study75 cited
  • 2024A scoping review of fair machine learning techniques when using real-world data61 cited
  • 2024Who gets the money? A qualitative analysis of fintech lending and credit scoring through the adoption of AI and alternative data57 cited
  • 2023Where is finance in the financialization of development?44 cited
  • 2023Evaluating Europe's push to enact AI regulations: how will this influence global norms?40 cited
  • 2024Rise of the Machines: The Impact of Automated Underwriting40 cited
  • 2024Ethical AI in Financial Inclusion: The Role of Algorithmic Fairness on User Satisfaction and Recommendation37 cited
  • 2024What drives the adoption of digital technology in the micro, small, and medium enterprises sector in a developing economy?33 cited
  • 2024Predicting financial distress in Latin American companies: A comparative analysis of logistic regression and random forest models

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26 cited
  • 2024Exploring trust determinants influencing the intention to use fintech via SEM approach: Evidence from Pakistan21 cited
  • 2024Streamlining COM-B model: Insights from the Healthy Eating Context20 cited
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