Do Unverifiable Disclosures Matter? Evidence from Peer-to-Peer Lending

By Jeremy Michels. 2012

287 citations recorded by the source corpus.

Subfields: Accounting, Finance

View Paper: https://www.semanticscholar.org/paper/525e6e6403b2d8d3d221fb1e5152f0f35e4f1e60

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Accounting

1. Catharine M. Lemieux
2. Nessrine Omrani
3. Huan Tang
4. Martin Peitz
5. Paul Belleflamme
6. Julapa Jagtiani

In Finance

1. Catharine M. Lemieux
2. Huan Tang
3. Julapa Jagtiani

Citations in the corpus

• Crowdfunding: A Literature Review and Research Directions (2014, unknown): “But, the poorer the credit ratings, the more soft facts are taken into account (Berkovich, 2011; Iyer et al., 2009; Michels, 2012).”
• Peer-to-Peer Lenders Versus Banks: Substitutes or Complements? (2019, background): “…literature on P2P lending focuses on investor behavior in relation to borrower characteristics such as appearance, disclosures, and social networks (Herzenstein, Sonenshein, and Dholakia 2011; Duarte, Siegel, and Young 2012; Michels 2012; Lin, Prabhala, and Viswanathan 2013; Freedman and Jin 2017).”
• Peer-to-Peer Crowdfunding: Information and the Potential for Disruption in Consumer Lending (2015, unknown): “Michels (2012) takes a different approach to narratives by codifying the potentially hard information available in narratives.”
• Do fintech lenders penetrate areas that are underserved by traditional banks? (2018, background): “Michels, J. (2012) “Do Unverifiable Disclosures Matter? Evidence from Peer-to-Peer Lending,” Accounting Review, 87(4):1385–1413. Morse, A. (2015) “Peer-to-Peer Crowdfunding: Information and the Potential for Disruption for Consumer Lending,” NBER Working Paper 20899.”
• The economics of crowdfunding platforms (2015, background): “Taking the borrowers point of view, Michels (2012) provides evidence that including more unveri able disclosures in a loan listing (e.g., intended use of proceeds, interest rates on other debts, explanations for poor credit ratings, or a picture) allows borrowers to obtain a lower interest rate on…”
• The roles of alternative data and machine learning in fintech lending: Evidence from the LendingClub consumer platform (2019, background): “Michels, J. (2012) “Do Unverifiable Disclosures Matter? Evidence from Peer-to-Peer Lending,” Accounting Review, 87(4):1385–1413. Morse, A. (2015) “Peer-to-Peer Crowdfunding: Information and the Potential for Disruption in Consumer Lending,” NBER Working Paper, www.nber.org/papers/w20899.pdf. Pope, D”