Despite financial markets’ growing interest, researchers and practitioners still struggle to transfer the blockchain concept introduced by Bitcoin to other application scenarios. To shed light on the technology’s ability to function as a transparency device in markets with asymmetric information, this study utilizes an adverse selection model to analyze its applicability as an information sharing arrangement in credit markets. In line with prior research, my findings indicate that sharing information about past entrepreneurial performance mitigates the impact of adverse selection effects on the banking side and reduces moral hazard of good entrepreneurs (plums) by generating a disciplinary effect. In addition, I identify an incentive for bad entrepreneurs (lemons) to behave opportunistically in order to be mistaken for plums when switching between banks. More specifically, the blockchain’s public record supplies them with information about the quality difference between plums and lemons, which allows them to optimize their mimicking. However, whether the additional information leads to an increase or decrease of moral hazard in total and under which circumstances the resulting behavior induces positive net utility gains and welfare effects depends on the characteristics of the market environment (e.g. quality differences, cost of capital, etc.). Eventually, the contribution of this study is threefold: First, it proposes an information system design that allows us to utilize the blockchain as a transparency device in credit markets. Second, it connects the technical characteristics of blockchain technology with previous findings about information dissemination in lemon markets and embeds it in the literature on information sharing arrangements. Third, it extends the current research on information sharing arrangements by providing an analytic evaluation of the impact of the public availability – one of the blockchain’s core features – of imperfect quality information in a market environment with asymmetric information and explicit quality differences. In total, this study aims to provide an initial guidance for the application of blockchain-based transparency devices, offers a first analytic assessment of the underlying economic mechanisms on the level of individual stakeholders, and indicates that greater transparency must not always be better.

1. KIT – University of the State of Baden-Wuerttemberg and
National Research Center of the Helmholtz Association
DokSem IISM 07.12.2017
www.kit.edu
FinteQC June 20 – June 21, 2018, Lévis
https://goo.gl/rzFU9b
The Blockchain, Plums, and Lemons
The Blockchain as a Transparency Device in the Market for Lemons
Benedikt Notheisen

2. 2
Central Blockchain Features & Registries
Distributed database
Decentralized consensus
mechanism
Cryptographic security
The Blockchain, Plums, and Lemons | Benedikt Notheisen
Key requirements of
registries:
Integrity 
Availability 
Interoperability 
Efficient reading 
Programmability 
Immutability 
[Tran et al., 2017]
[Nakamoto, 2008; Lamport et al., 1982; Szabo, 1997; Xu et al., 2016; Notheisen et al., 2017b]

3. 3
Plums and Lemons
The Blockchain, Plums, and Lemons | Benedikt Notheisen
“A choice investment, or one that has
outperformed other comparable investments.”
https://www.investopedia.com/terms/p/plum.asp
“A lemon is a very disappointing investment in
which your expected return is not even close to
being achieved [...]”.
https://www.investopedia.com/terms/l/lemon.asp
Due to asymmetric information, the uncertainty about quality among opposing
market participants leads to inefficient market outcomes and moral hazard.
[Stiglitz & Weiss, AER, 1981; Akerlof, QJE, 1970; Karlan & Zinman, ECRA, 2009; Kirschenmann, JFI, 2016]

4. 4
The Blockchain as a Transparency Device
The Blockchain, Plums, and Lemons | Benedikt Notheisen
“[Blockchain-based information sharing] reduces [the negative effects
of] uncertainty about quality […] in lemon markets by providing a
reliable, transparent, and complete record of each asset’s history [to all
users of the system].”
[Notheisen et al., 2017]

5. 5
The Blockchain as a Transparency Device
The Blockchain, Plums, and Lemons | Benedikt Notheisen
“[Blockchain-based information sharing] reduces [the negative effects
of] uncertainty about quality […] in lemon markets by providing a
reliable, transparent, and complete record of each asset’s history [to all
users of the system].”
[Notheisen et al., 2017]
[Pagano & Jappelli, JF, 1993; Djankov et al., JFE, 2007; Barth et al., RFS, 2009; Doblas-Madrid & Minetti, JFE,
2013; …]
[Padilla & Pagano, RFS, 1997; Padilla & Pagano, EER, 2000; Hertzberg et al., JF, 2009; Sharma, JEBO, 2017;
Gianetti et al, RFS, 2017; Diamond, JPE, 1989; Vercammen, Eco, 1995; …]

6. 6
The Blockchain as a Transparency Device
The Blockchain, Plums, and Lemons | Benedikt Notheisen
“[Blockchain-based information sharing] reduces [the negative effects
of] uncertainty about quality […] in lemon markets by providing a
reliable, transparent, and complete record of each asset’s history [to all
users of the system].”
[Notheisen et al., 2017]
How does the public availability of quality information affect
the behavior of lemons?
RQ 1
How does this behavior affect market outcomes?RQ 2

7. 7
The Model
The Blockchain, Plums, and Lemons | Benedikt Notheisen

8. 8
The Model
The Blockchain, Plums, and Lemons | Benedikt Notheisen
𝜃 1 − 𝜃

9. 9
The Model
The Blockchain, Plums, and Lemons | Benedikt Notheisen

10. 10
The Entrepreneurs
The Blockchain, Plums, and Lemons | Benedikt Notheisen
ҧ𝑝
𝑉𝐻( ҧ𝑝)
𝑉𝐿( ҧ𝑝)
Disutility of effort

11. 11
The Entrepreneurs
The Blockchain, Plums, and Lemons | Benedikt Notheisen
ҧ𝑝
𝑉𝐻( ҧ𝑝)
𝑉𝐿( ҧ𝑝)
𝑈 𝐻(pH
∗
)
𝑝 𝐻
∗
𝑈𝐿(pL
∗
)
𝑝 𝐿
∗
Disutility of effort Utility

12. 12
The Model
The Blockchain, Plums, and Lemons | Benedikt Notheisen

13. 13
The Model
The Blockchain, Plums, and Lemons | Benedikt Notheisen
𝑝𝑖 1 − 𝑝𝑖

14. 14
The Model
The Blockchain, Plums, and Lemons | Benedikt Notheisen
[Chakravarty et al., 2004, JEP; Manrai & Manrai, JRCS 2007;
Keaveney, JM, 1995; Kiser, JIO, 2002; Ioannidou & Ongena, JF, 2010]
[Padilla & Pagano, EER, 2000]

15. 15
The Model
The Blockchain, Plums, and Lemons | Benedikt Notheisen

16. 16
The Model
The Blockchain, Plums, and Lemons | Benedikt Notheisen

17. 17
Solution Concept
The Blockchain, Plums, and Lemons | Benedikt Notheisen
Backward induction to find the subgame perfect equilibria.

18. 18
Assessment of Outside Entrepreneurs in t = 2
The Blockchain, Plums, and Lemons | Benedikt Notheisen
Banks use Bayes’ rule to update their
beliefs about outside plums and lemons.
Banks underestimate the average
success probabilities of defaulters
and overestimate the average
success probabilities of non-
defaulters

19. 19
Assessment of Outside Entrepreneurs in t = 2
The Blockchain, Plums, and Lemons | Benedikt Notheisen

20. 20
Interest Rates in Period 2
The Blockchain, Plums, and Lemons | Benedikt Notheisen
Successful
inside plums
Successful
switchers
Defaulted
inside plums
Defaulted
switchers
Inside
lemons
Perfect
Transparency
Perfect
TransparencyFull opacity
Succes-
sors
Defaulters

21. 21
Interest Rates in Period 2
The Blockchain, Plums, and Lemons | Benedikt Notheisen
Full opacity
Successful
inside plums
Successful
switchers
Defaulted
inside plums
Defaulted
switchers
Inside
lemons
Reduction of the
adverse selection
effect

22. 22
Interest Rates in Period 2
The Blockchain, Plums, and Lemons | Benedikt Notheisen
Successful
inside plums
Successful
switchers
Defaulted
inside plums
Defaulted
switchers
Inside
lemons
Informational
monopoly rents
Perfect
Transparency
Perfect
Transparency

23. 23
The Disciplinary Effect [Padilla & Pagano, EER, 2000]
The Blockchain, Plums, and Lemons | Benedikt Notheisen

24. 24
The Disciplinary Effect [Padilla & Pagano, EER, 2000]
The Blockchain, Plums, and Lemons | Benedikt Notheisen
Successful
inside plums
Successful
switchers
Defaulted
inside plums
Defaulted
switchers
Inside
lemons
Alleviation of
moral hazard

25. 25
Opportunistic Effect
The Blockchain, Plums, and Lemons | Benedikt Notheisen

26. 26
Opportunistic Effect
The Blockchain, Plums, and Lemons | Benedikt Notheisen
Successful
inside plums
Successful
switchers
Defaulted
inside plums
Defaulted
switchers
Inside
lemons
Increase of moral
hazard

27. 27
Conclusion
The Blockchain, Plums, and Lemons | Benedikt Notheisen
Next Steps
How does the publicly availability of quality information
affect the behavior of lemons?
RQ 1
• Confirmation of previous results in a more sophisticated setting.
• Interest rates incentivize lemons to be mistaken for plums.
• Publicly available information about plums and lemons allows them to
determine how much effort they have to invest to be mistaken.
Which factors constrain and
which factors facilitate moral
hazard of lemons (RQ 1.2) ?
Determine the trade-off between the moral
hazard effects of plums and lemons? (RQ 2.1)
What is the welfare implication? (RQ 2.2)
Implications for the design of
the information sharing
mechanism?

28. 28
References
Akerlof, George (1970): The Market for Lemons. Qualitative Uncertainty and the Market
Mechanism. In Quarterly Journal of Economics 84 (3).
Barth, James R.; Lin, Chen; Lin, Ping; Song, Frank M. (2009): Corruption in bank lending to
firms. Cross-country micro evidence on the beneficial role of competition and information sharing☆.
In Journal of Financial Economics 91 (3), pp. 361–388. DOI: 10.1016/j.jfineco.2008.04.003.
Chakravarty, Sugato; Feinberg, Richard; Rhee, Eun-Young (2004): Relationships and individuals'
bank switching behavior. In Journal of Economic Psychology 25 (4), pp. 507–527. DOI:
10.1016/S0167-4870(03)00051-5.
Diamond, Douglas W. (1989): Reputation Acquisition in Debt Markets. In Journal of Political
Economy 97 (4), pp. 828–862. DOI: 10.1086/261630.
DJANKOV, S.; MCLIESH, C.; SHLEIFER, A. (2007): Private credit in 129 countries☆. In Journal
of Financial Economics 84 (2), pp. 299–329. DOI: 10.1016/j.jfineco.2006.03.004.
Doblas-Madrid, Antonio; Minetti, Raoul (2013): Sharing information in the credit market.
Contract-level evidence from U.S. firms. In Journal of Financial Economics 109 (1), pp. 198–223.
DOI: 10.1016/j.jfineco.2013.02.007.
Giannetti, Mariassunta; LIBERTI, JOSÉ MARÍA; Sturgess, Jason (2017): Information Sharing
and Rating Manipulation. In Rev. Financ. Stud. 30 (9), pp. 3269–3304. DOI: 10.1093/rfs/hhx050.
HERTZBERG, ANDREW; LIBERTI, JOSÉ MARÍA; PARAVISINI, DANIEL (2011): Public
Information and Coordination. Evidence from a Credit Registry Expansion. In The Journal of Finance
66 (2), pp. 379–412. DOI: 10.1111/j.1540-6261.2010.01637.x.
IOANNIDOU, VASSO; ONGENA, STEVEN (2010): “Time for a Change”. Loan Conditions and
Bank Behavior when Firms Switch Banks. In The Journal of Finance 65 (5), pp. 1847–1877. DOI:
10.1111/j.1540-6261.2010.01596.x.
Karlan, Dean; Zinman, Jonathan (2009): Observing Unobservables. Identifying Information
Asymmetries With a Consumer Credit Field Experiment. In Econometrica 77 (6), pp. 1993–2008.
DOI: 10.3982/ECTA5781.
Keaveney, Susan M. (1995): Customer Switching Behavior in Service Industries. An Exploratory
Study. In Journal of Marketing 59 (2), p. 71. DOI: 10.2307/1252074.
Kirschenmann, Karolin (2016): Credit rationing in small firm-bank relationships. In Journal of
Financial Intermediation 26, pp. 68–99. DOI: 10.1016/j.jfi.2015.11.001.
Kiser, Elizabeth K. (2002): Predicting Household Switching Behavior and Switching Costs at
Depository Institutions. In Review of Industrial Organization 20 (4), pp. 349–365. DOI:
10.1023/A:1015692910277.
Manrai, Lalita A.; Manrai, Ajay K. (2007): A field study of customers’ switching behavior for bank
services. In Journal of Retailing and Consumer Services 14 (3), pp. 208–215. DOI:
10.1016/j.jretconser.2006.09.005.
Notheisen, Benedikt; Cholewa, Jacob Benjamin; Shanmugam, Arun Prasad (2017): Trading
Real-World Assets on Blockchain. In Bus Inf Syst Eng 59 (6), pp. 425–440. DOI: 10.1007/s12599-
017-0499-8.
Padilla, A. Jorge; PAGANO, MARCO (1997): Endogenous Communication Among Lenders and
Entrepreneurial Incentives. In Rev. Financ. Stud. 10 (1), pp. 205–236. DOI: 10.1093/rfs/10.1.205.
Padilla, A.Jorge; PAGANO, MARCO (2000): Sharing default information as a borrower discipline
device. In European Economic Review 44 (10), pp. 1951–1980. DOI: 10.1016/S0014-2921(00)00055-
6.
PAGANO, MARCO; JAPPELLI, TULLIO (1993): Information Sharing in Credit Markets. In The
Journal of Finance 48 (5), pp. 1693–1718. DOI: 10.1111/j.1540-6261.1993.tb05125.x.
Sharma, Priyanka (2017): Is more information always better? A case in credit markets. In
Journal of Economic Behavior & Organization 134, pp. 269–283. DOI: 10.1016/j.jebo.2016.12.002.
Stiglitz, Joseph E.; Weiss, Andrew (1981): Credit rationing in markets with imperfect information.
In The American economic review 71 (3), pp. 393–410.
Tran, An Binh; Weber12, Xiwei Xu12 Ingo; Staples12, Mark; Rimba, Paul (2017): Regerator. A
Registry Generator for Blockchain. In CAiSE.
Vercammen, James A. (1995): Credit Bureau Policy and Sustainable Reputation Effects in Credit
Markets. In Economica 62 (248), p. 461. DOI: 10.2307/2554671.
…
The Blockchain, Plums, and Lemons | Benedikt Notheisen

29. 29 The Economics of Blockchain in Finance | Benedikt Notheisen
Thank you for your attention!
Benedikt Notheisen
Karlsruhe Institute of Technology
Institute of Information System and Marketing
benedikt.notheisen@kit.edu

30. 30
BACKUP
The Blockchain, Plums, and Lemons | Benedikt Notheisen

31. 31
The Economy
The Blockchain, Plums, and Lemons | Benedikt Notheisen
• Players
• Single bank
• Continuum of investors
Information flow
Cash flow
Blockchain
Standardized data
Banks
Investor-
specific data
Investor-specific
data
Bank-specific
data
Borrower-lender
relationship 𝜃
Entrepreneurs
0 1

32. 32
Blockchain-Based Information Sharing
The Blockchain, Plums, and Lemons | Benedikt Notheisen
Blockchain
Application Application
Payout Decision +
conditions
t
Payout
Investor-specific
information
Loan
Repayment
E600BF9CFC913B8A31C81
19F6AC96A78514F9C136E8
77AB4261957341D012463
E600BF9CFC913B8A31C81
19F6AC96A78514F9C136E8
77AB4261957341D012463
E600BF9CFC913B8A31C81
19F6AC96A78514F9C136E8
77AB4261957341D012463
Loan
E600BF9CFC913B8A31C81
19F6AC96A78514F9C136E8
77AB4261957341D012463
4381DC2AB14285160C8086
59AEE005D51255ADD7264
B318D07C7417292C7442C
4381DC2AB14285160C8086
59AEE005D51255ADD7264
B318D07C7417292C7442C

33. 33
[Wüst and Gervais, 2017; Notheisen et al, 2017]
Public & permissioned setup
Why DLT as CIS?
The Blockchain, Plums, and Lemons | Benedikt Notheisen
Credit Information System
Standardized data
𝜃
Entrepreneurs
Banks
Writer &
Reader
Writer
Adverse
Selection
Moral
Hazard
Do we need DLT?
Storage of transactional data 
Multiple writing parties 
Always online TTP 
Known identity of writing
parties

Mutually mistrusting writing
parties

Asymmetric information 
Corporate
ID
Corporate/
personal ID

34. 34
The Entrepreneurs
The Blockchain, Plums, and Lemons | Benedikt Notheisen
Exp. utility in period 1 Exp. utility in period 2
Disutility of effort in period 1 Disutility of effort in period 2

35. 35
The Entrepreneurs
The Blockchain, Plums, and Lemons | Benedikt Notheisen
ҧ𝑝
𝑉𝐻( ҧ𝑝)
𝑉𝐿( ҧ𝑝)
Exp. utility in period 1 Exp. utility in period 2
Disutility of effort in period 1 Disutility of effort in period 2

36. 36
The Entrepreneurs
The Blockchain, Plums, and Lemons | Benedikt Notheisen
ҧ𝑝
𝑉𝐻( ҧ𝑝)
𝑉𝐿( ҧ𝑝)
Exp. utility in period 1 Exp. utility in period 2
Disutility of effort in period 1 Disutility of effort in period 2
𝑈 𝐻(pH
∗
)
𝑝 𝐻
∗
𝑈𝐿(pL
∗
)
𝑝 𝐿
∗

37. 37
Probability Structure
The Blockchain, Plums, and Lemons | Benedikt Notheisen
𝜃
1 − 𝜃
𝑝 𝐻
1 − 𝑝 𝐻
𝐻
Good entrepreneur
𝑅 > 0
𝑅 = 0
𝑝 𝐿
1 − 𝑝 𝐿
𝐿
Bad entrepreneur
𝑅 > 0
𝑅 = 0