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Online peer-to-peer (P2P) lending, where individual investors provide unsecured loans directly to individual borrowers without the intermediation of banks, has experienced rapid growth in recent years. One of its defining features is the presence of social networks, which could provide important credit information about borrowers. Drawing on the literature in finance and social networks, I study whether and how network metrics affect the outcome of financial transaction in this market, and whether such credit-worthiness is supported ex post through loan performance data. Results show that relational aspects of the online social network help mitigate information asymmetry in the lending process, and that a critical success factor of the industry is to better reveal and utilize the soft credit information embedded in social networks.
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Stored only when both papers are in the corpus — 33 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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