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Using your regular contacts as collateral: The information value of call logs

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  • He, Yunwen

Abstract

This paper aims to uncover the deterrent effect of external social ties on online peer-to-peer lending by extracting valuable information from the phone usage data. Contrary to the studies viewing online internal friendships as the signal of credit quality, we find that the total number of outgoing calls made in the month before loan requests is positively associated with the probability of default, which suggests that more social interactions offline mediated by mobile phones are more likely to signal poor trustworthiness. Only the features pertaining to the calls made during the morning for a given day have the potential as an effective predictor for the borrower’s credible social collateral. However, the online peer-to-peer lending platform studied by us fails to perfectly judge borrowers by their external social ties since the total number of outgoing calls generally has a negative relationship with the interest rates charged for funded loans. Overall, our work advances the understanding of the economic value carried by call logs in the context of disintermediated financial markets with information asymmetry.

Suggested Citation

  • He, Yunwen, 2021. "Using your regular contacts as collateral: The information value of call logs," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    • Handle: RePEc:eee:ecofin:v:58:y:2021:i:c:s1062940821001005
    DOI: 10.1016/j.najef.2021.101480
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    References listed on IDEAS

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    1. Chen, Cathy W.S. & Dong, Manh Cuong & Liu, Nathan & Sriboonchitta, Songsak, 2019. "Inferences of default risk and borrower characteristics on P2P lending," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
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    10. Jon Kleinberg & Himabindu Lakkaraju & Jure Leskovec & Jens Ludwig & Sendhil Mullainathan, 2018. "Human Decisions and Machine Predictions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(1), pages 237-293.
    11. Sigrist, Fabio & Hirnschall, Christoph, 2019. "Grabit: Gradient tree-boosted Tobit models for default prediction," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 177-192.
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    More about this item

    Keywords

    Peer-to-peer lending; Phone usage; External social ties; Information asymmetry;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • G1 - Financial Economics - - General Financial Markets

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