1. Discussion of “The Role of Hard and Soft Information in Peer-to-Peer Lending” by Ester Faia and Monica Paiella
Balgobin Y., Telecom ParisTech
10th Financial Risks International Forum
March 27, 2017

2. Summary of paper

3. Summary of paper Main question:
Does the existence of hard and soft information improve Peer-to-Peer (P2P) lending?

4. Summary of paper Main question:
Does the existence of hard and soft information improve Peer-to-Peer (P2P) lending?
Signaling allows for better loan spreads and liquidity premia, and an overall increased participation in P2P lending.

5. Summary of paper Main question: General equilibrium model
Does the existence of hard and soft information improve Peer-to-Peer (P2P) lending?
Signaling allows for better loan spreads and liquidity premia, and an overall increased participation in P2P lending.
General equilibrium model
Econometrical analysis using a dataset from Prosper.com

6. Summary of paper
P2P lending is characterized by asymmetric information: how to distinguish between good and bad quality projects?

7. Summary of paper
P2P lending is characterized by asymmetric information: how to distinguish between good and bad quality projects?
However, loan spreads similar or even competitive with the banking sector.

8. Summary of paper
P2P lending is characterized by asymmetric information: how to distinguish between good and bad quality projects?
However, loan spreads similar or even competitive with the banking sector.
What is then the role played by information available on P2P platforms?

9. Summary of paper
On P2P lending platforms, several indicators help to reduce asymmetric information between borrowers and investors.

10. Summary of paper
On P2P lending platforms, several indicators help to reduce asymmetric information between borrowers and investors.
Hard information: FICO score, number of credit inquiries, Prosper rating and Prosper score.

11. Summary of paper
On P2P lending platforms, several indicators help to reduce asymmetric information between borrowers and investors.
Hard information: FICO score, number of credit inquiries, Prosper rating and Prosper score.
Soft information : dummies for group membership and recommandations/funding from « Prosper friends ».

12. The model
Choice between P2P lending and banking sector for both borrowers and investors.
Investors solve a portfolio model.

13. The model
Choice between P2P lending and banking sector for both borrowers and investors.
Investors solve a portfolio model.
Signaling introduced as affecting positively the subjective probability of a project’s success.

14. The model
Choice between P2P lending and banking sector for both borrowers and investors.
Investors solve a portfolio model.
Signaling introduced as affecting positively the subjective probability of a project’s success.
Lower liquidity premia required and increased liquidity on the market.

15. The model
Choice between P2P lending and banking sector for both borrowers and investors.
Investors solve a portfolio model.
Signaling introduced as affecting positively the subjective probability of a project’s success.
Lower liquidity premia required and increased liquidity on the market.
More participation in the market and higher share of P2P investments in household’s portfolio.

16. The model - Comments
No distinction between hard and soft information.

17. The model - Comments No distinction between hard and soft information.
Cost of using information?

18. Econometrics OLS regressions: determinants of lending rates.
Hard information: FICO score, number of credit inquiries, Prosper rating and Prosper score.
Soft information : dummies for group membership and recommendations/funding from « Prosper friends ».

19. Econometrics OLS regressions: determinants of lending rates.
Hard information: FICO score, number of credit inquiries, Prosper rating and Prosper score.
Soft information : dummies for group membership and recommendations/funding from « Prosper friends ».
Hard information: the riskier the borrower, the higher the rate.

20. Econometrics OLS regressions: determinants of lending rates.
Hard information: FICO score, number of credit inquiries, Prosper rating and Prosper score.
Soft information : dummies for group membership and recommendations/funding from « Prosper friends ».
Hard information: the riskier the borrower, the higher the rate.
Soft information mostly non significant if number of previous loans is included.

21. Econometrics OLS regressions: determinants of lending rates.
Hard information: FICO score, number of credit inquiries, Prosper rating and Prosper score.
Soft information : dummies for group membership and recommendations/funding from « Prosper friends ».
Hard information: the riskier the borrower, the higher the rate.
Soft information mostly non significant if number of previous loans is included.
 Difficult to assess the real effect of soft information on lending rates.