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Machine Learning in support of credit scoring overcoming traditional predictive models. What do we know so far?

  • Manta Francesco
  • , Calò Lorenzo
  • , Stefanelli Valeria
  • , Matteo Cotugno
  • , Boscia Vittorio

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This chapter examines the use of machine learning (ML) models in credit scoring and risk assessment, comparing their efficiency and accuracy to traditional methods. The discussion highlights ML's potential to enhance credit evaluations, particularly in areas like peer-to-peer lending and non-traditional financial products. The analysis emphasizes the operational benefits of adopting ML in credit processes.
Original languageEnglish
Title of host publicationInnovation in Banking and Financial Intermediaries
PublisherRoutledge
Pages189-215
Number of pages27
ISBN (Print)9781032887968
Publication statusPublished - 2025

Keywords

  • machine learing
  • credit scroring

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