Success factors in peer-to-business (P2B) crowdlending: A predictive approach

Antonio M. Moreno-Moreno, Carlos Sanchis-Pedregosa, Emma Berenguer

Research output: Contribution to journalArticle in a journalpeer-review

1 Scopus citations

Abstract

Peer-to-Business (P2B) crowdlending is gaining importance among companies seeking funding. However, not all projects get the same take-up by the crowd. Thus, this study aims to determine the key factors that drive non-professional investors to choose a given loan in an online environment. To this purpose, we have analyzed 243 crowdlending campaigns on October.eu platform. We have obtained a series of variables from the analyzed loans using logistic regression. Results indicate that loan amount, loan term and overall credit rating are the key predictors of non-professional lender P2B crowdlending success. These findings may be useful for predicting whether the crowd will subscribe to a loan request or not. This information would help businesses to modify specific loan characteristics (if possible) to make their loans more attractive or could even lead companies to consider a different financial option. It could also help platforms select and adapt project parameters to secure their success.
Original languageEnglish
Article number8864063
Pages (from-to)148586-148593
Number of pages8
JournalIEEE Access
Volume7
DOIs
StatePublished - 1 Jan 2019

Bibliographical note

Publisher Copyright:
© 2013 IEEE.

Keywords

  • Crowdfunding
  • crowdlending
  • institutional lenders
  • logistic regression
  • non-professional lenders
  • peer-to-business (P2B)

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