La Revue des Sciences Commerciales
Volume 24, Numéro 2, Pages 147-167
2025-12-26
Ai-enhanced Risk Assessment In P2p Lending: Advancing Effectiveness And Inclusivity In Credit Evaluation.
Authors : Akboudj Nouha Nor Djihane . Lebsaira Meriem .
Abstract
This study examines AI applications in P2P lending credit evaluation, addressing traditional methods’ limitations in handling complex borrower data. Using comparative analysis and case studies from LendingClub, the European P2P lending, and the Chinese P2P lending market, the research evaluates AI versus conventional models. Results show AI’s superior predictive accuracy, efficiency, and inclusion capabilities, particularly in default prediction and fraud detection. However, challenges include algorithmic transparency, interpretability, and fairness concerns. The study concludes hybrid approaches combining traditional interpretability with AI predictive power offer optimal solutions for responsible credit management.
Keywords
Artificial intelligence ; Peer-to-peer lending ; credit risk evaluation ; machine learning.
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