A trust model for online peer-to-peer lending: a lender’s

Click here to load reader

  • date post

  • Category


  • view

  • download


Embed Size (px)

Transcript of A trust model for online peer-to-peer lending: a lender’s

A trust model for online peer-to-peer lending: a lender’s perspective
Dongyu Chen • Fujun Lai • Zhangxi Lin
Published online: 31 May 2014
Springer Science+Business Media New York 2014
Abstract Online peer-to-peer (P2P) lending is a new but
essential financing method for small and micro enterprises
that is conducted on the Internet and excludes the involve-
ment of collateral and financial institutions. To tackle the
inherent risk of this new financing method, trust must be
cultivated. Based on trust theories, the present study devel-
ops an integrated trust model specifically for the online P2P
lending context, to better understand the critical factors that
drive lenders’ trust. The model is empirically tested using
surveyed data from 785 online lenders of PPDai, the first and
largest online P2P platform in China. The results show that
both trust in borrowers and trust in intermediaries are sig-
nificant factors influencing lenders’ lending intention.
However, trust in borrowers is more critical, and not only
directly nurtures lenders’ lending intention more efficiently
than trust in intermediaries, but also carries the impact of
trust in intermediaries on lenders’ lending intention. To
develop lenders’ trust, borrowers should provide high-
quality information for their loan requests and intermediaries
should provide high-quality services and sufficient security
protection. The findings provide valuable insights for both
borrowers and intermediaries.
1 Introduction
(SMEs) in an effective and efficient way has attracted
much attention from both academics and practitioners. The
financing problem is especially critical in developing
countries like China. According to a report from the Chi-
nese Government Research Center, approximately 50 % of
SMEs in China face financial constraints. With advances in
information technologies, a new type of financing method,
online peer-to-peer (P2P) lending has, since 2005, become
an important supplement to traditional financing. Online
P2P lending allows people to lend and borrow funds
directly through an online intermediary without the medi-
ation of financial institutes.
years around the world, including the UK., the US, Japan,
Sweden, Canada, and China [1]. Prosper.com, one of the
largest online lending intermediaries in the world, has
attracted over 1 million members and facilitated over
32,000 loans, totaling over $193 million [2]. As a leading
platform in China, PPDai (www.PPDai.com) has attracted
500,000 members and facilitated about 100 million RMB
in loans in 2011.
First, the ‘‘goods’’ exchanged on online P2P platforms are
neither tangible products nor services, but rather the rights
to claim principle and interests in the future. Second,
lenders make lending decisions mainly based on the risks
and benefits of a lending transaction rather than on the
D. Chen F. Lai
Suzhou 215000, China
Long Beach, MS 39560, USA
e-mail: fujun.lai@usm.edu
Z. Lin
University, Lubbock, TX 79409, USA
e-mail: zhangxi.lin@ttu.edu
DOI 10.1007/s10799-014-0187-z
e-commerce for product and service exchange are not
readily applied to online P2P lending settings. In traditional
consumer-to-consumer (C2C) e-commerce (e.g. Taobao in
China and eBay in the US), the intermediaries hold the
funds from buyers and transfer them to sellers only after
the buyer confirms they have received the product or ser-
vice. Such an escrow system cannot be applied in online
P2P lending because the funds themselves are the exchange
object. Therefore, the transactional behaviors of online P2P
lending may not be the same as those in traditional
e-commerce business settings. In addition, previous studies
have mainly focused on developed countries, whose results
may not be applicable to Chinese settings. To better
understand the lending behaviors in China’s online P2P
lending platforms, further research on China’s online P2P
lending is warranted.
Online P2P lending is inherently high risk; it is not only
characterized by uncertainty, but also by anonymity, lack
of control, and potential opportunism [3]. On online P2P
lending platforms, lenders and borrowers are not able to
communicate face-to-face and funds trading is conducted
online. There is a high level of information asymmetry
between borrowers and lenders [4], which presents a sig-
nificant barrier to the further development of this market-
place. P2P lending faces a variety of risks either from the
implicit uncertainty of using a sophisticated technological
infrastructure or from the conduct of borrowers involved in
online transaction [3]. Prior studies have also reported that
trust plays a central role in online transactions [5–8].
Therefore, initiating trust between borrowers and lenders is
a critical issue for online P2P lending. Previous studies
have investigated the antecedents of trust from a variety of
perspectives in the e-commerce context, such as online
purchasing (e.g., [8–10]), the adoption of Internet banking
(e.g., [11]), mobile payment (e.g., [12, 13]), and virtual
community development (e.g., [14, 15]). However, few
studies consider this issue in the context of the online P2P
lending marketplace.
The remainder of this paper is organized as follows. We
first briefly present the background of online P2P lending
and then review the related literature, followed by devel-
oping a conceptual model with hypotheses. Subsequently,
we present the research methodology and test the hypoth-
eses. Finally, we discuss the findings and implications and
make a conclusion.
There are several commercial lending platforms, such as
Prosper, PPDai, Lending Club, Zopa, and Easycredit (see
Table 1). These platforms employ similar lending proce-
dures. The potential user who intends to borrow or lend
must create an account, providing personal information,
such as name, address, phone numbers, and social security
number. Some online P2P lending platforms (e.g., Prosper)
also require users to provide bank account information. The
information is then verified and a credit number is assigned
accordingly. For members of Prosper, a credit score is
extracted directly from Fair, Isaac Credit Organization
(FICO). However, there is no such agency to provide credit
scores in China, so borrowers’ credit scores are calculated
based on the information they provide, such as ID number,
bank account, income, age, and occupation.
Borrowers deemed creditworthy are invited to create their
borrowing listings. The listings are essentially loan requests
that specify the amount they seek, the maximum interest rate
they will pay, and other optional information, such as free-
format descriptions of loan purpose. Lenders make lending
decisions according to the listing information and the bor-
rower’s personal information. On most P2P lending platforms,
such as Prosper in the US and PPDai in China, a lender
chooses to finance only a portion of a loan, rather than the
entire loan. For instance, a lender can bid a minimum amount
of $50 on Prosper. Borrowers can choose either a closed or
open auction format. In the closed format, the auction closes as
soon as the total amount requested is reached. The loan’s
interest rate is that specified by the borrower in the listing. In
the open format, the auction is open for a pre-assigned period.
Even if the entire amount requested is funded, lenders can
continue to bid down the interest rate.
Once the bidding process ends, the listing is closed and
submitted to the lending intermediary for further review
[1]. Borrowers may be asked to provide additional docu-
mentation and information. If the lending is approved,
funds are directly transferred from the winning bidder’s
account to the borrower’s account. In general, service fees
are charged to both borrowers and lenders by the inter-
mediary. The borrower’s payback is also directly trans-
ferred from the borrower’s account to the lender’s account.
If the payback is overdue beyond a pre-determined limit,
such as 2 months on Prosper, the borrower’s default will be
recorded and submitted to credit bureaus and then debt
collection is initiated.
Although P2P lending has been growing rapidly in
China, it is still in the initial stages of development. The
first online P2P lending platform, PPDai (ppdai.com), was
established in July 2007. Due to differences in legislation,
credit systems, and network security, many unique prob-
lems face China’s online P2P lending that may not exist in
developed countries. The most important problem is the
lack of a legal basis in the supervision of online P2P
lending intermediaries and the lack of safety guarantees for
lenders [16].
Several studies have been conducted on the behaviors of
online P2P. Based on open data from Prosper, researchers
have found that information from borrowers and loan
requests are critical to lenders’ decisions. For instance, Lin
[17] revealed that the lower the credit level of a borrower,
the less likely his/her loan listing will be funded. Collier
and Hampshire [18] discovered that information of both
loan amount and debt/income ratio of a borrower influence
the final interest rate of a loan. Some scholars have also
found that the social relationship information of a borrower
influences loan success, interest rate, and default proba-
bility. For example, Lin et al. [4] found that the relational
aspect of social capital is a reliable signal that indicates a
borrower’s trustworthiness. Greiner and Wang [19] pointed
out that social capital plays a more important role for
borrowers with lower credit levels.
Although P2P lending has been attracting increasing
interests from practitioners in China, research on it is still
scarce, theoretical studies in particular. Among them, for
example, Chen et al. [20] explored the critical antecedents
of lenders’ trust in borrowers in China and found that
structural social capital, relational social capital, and dis-
position to trust are important in initiating trust in the
lending process. Xu et al. [21] made a comparison of the
online lending marketplace between China and other
countries and found that cultural factors may influence
online lending business models as well as lenders’
High risk is inherent in P2P lending, in particular for
lenders. It is vital for lenders to identify credible borrowers
and choose the right lending intermediary. On this basis,
for P2P lending to succeed, trust must be established at the
very beginning [10]. Therefore, it is critical to investigate
the key factors in lenders’ trust-building processes.
4.1 Conceptual model
Trust is a complex behavior, which has been defined from
several different perspectives in a variety of disciplines.
For instance, in psychology, trust is defined as an expec-
tation that ‘‘an exchange partner will not engage in
opportunistic behavior, despite short-term incentives and
uncertainties about long-term rewards’’ [22]. In sociology,
it is defined as ‘‘a particular level of the subjective prob-
ability with which an agent assesses that another agent or
group of agents will perform a particular action, both
before such action can be monitored and in a context in
which it affects his own action’’ [23]. In management
areas, trust is defined as the willingness of a party to be
vulnerable to the actions of another party based on the
expectation that the other will perform a particular action
important to the trustor, irrespective of their ability to
monitor or control the other party [24].
When there is uncertainty as to how others will behave,
trust is a prime determinant of what people expect from the
situation and how they behave [10]. Therefore, trust is a
Table 1 Online P2P lending
intermediaries Region Intermediary Start
Zopa, LendingClub, VirginMoneyus,
Loanio, Mircroplace, Fynanz
2007 PPDai, Qifang,
Zidisha 2009 ChangDai 2010
Multi-national Kiva 2005 UK Zopa 2005
Microplace 2007 FundingCircle 2010
Boober 2007 CommunityLend 2008
Monetto 2008 Denmark Fairrates 2007
Australia IGrin 2007 Holland Boober 2007
Sweden Loanland 2007 Africa MyC4 2006
Germany Smava 2007
e-commerce. In the online P2P context, trust is critical in
fulfilling lending transactions because of the high risk of
borrowers engaging in opportunistic behaviors. Although
there are no studies on trust building in the online P2P lending
context, there are a number of studies on trust building in other
related contexts, such as e-commerce e.g., [25–27].
In the literature, trust has been examined through the
framework of ‘‘antecedents–trust–outcomes’’ [28]. In this
framework, trust is conceptualized as specific trust beliefs
and general trust beliefs [24, 29]. Specific trust beliefs deal
primarily with the characteristics of trustees, while general
trust beliefs deal primarily with the overall impressions of
trustees [10]. Specific trust beliefs are framed as anteced-
ents to general trust beliefs [24, 30] and general trust
beliefs lead to behavioral intention [31]. Gefen et al. [10]
thought that the distinction between specific and general
trust beliefs was applicable in the context of online trans-
actions. Therefore, we frame our conceptual model with
specific trust beliefs as antecedents of general trust beliefs
and behavioral intention as the outcome of general trust
beliefs, as depicted in Fig. 1.
The model is contextualized to the online P2P context,
where specific trust beliefs are delineated as knowledge-
based, institution-based, and cognition-based, while gen-
eral trust beliefs are described as trust in intermediary and
trust in borrower. Various variables are contextualized for
the specific trust beliefs in the online P2P context. For
example, familiarity is a variable for a knowledge-based
specific trust belief, service quality and safety as institu-
tional-based and social capital and information quality as
cognition-based specific trust beliefs. These specific and
general trust beliefs are further deliberated as follows.
4.2 Specific trust beliefs
In the context of e-commerce, Gefen et al. [10] identified
specific trust beliefs as cognition-based, institution-based,
knowledge-based, calculative-based, and personality-
based. The first four types of trust antecedents are mainly
relevant either to the characteristics of trustees or to the
relationships between trustees and trustors, while person-
ality-based trust relates to the personalities of trustors and
is irrelevant to trustees [29, 31].
Fig. 1 Conceptual model. Solid lines hypothesized relationships; Dashed lines controls; Glow boxes specific trust beliefs; Bevel boxes general
trust beliefs; 3D Rotation box outcome trust belief
242 Inf Technol Manag (2014) 15:239–254
of characteristics demonstrated by trustees. Individuals
assess trustee’s trustworthiness based on first impressions
through second-hand information [32], and tend to place
more trust in people similar to themselves [10]. This kind
of trusting belief is formed via categorization and illusions
of control [10]. Overall, cognition-based trust is utilized to
gain some sense of control in an uncertain situation when a
trustor has no prior first-hand experience with the trustee
ing intermediaries), and refers to the trust based on guar-
antees and commendations from third parties [33]. Such
institution-based trust is ‘‘especially suited for online
marketplaces where buyers predominantly transact with
new and unknown sellers under the aegis of third parties
who provide an institutional context’’ [34, p. 38].
Knowledge-based trust antecedents suggest that trust
develops as a result of the aggregation of trust-related
knowledge by the parties involved [35]. Once a trustor
obtains sufficient knowledge and information of the trustee,
he is more likely to engage in trustworthiness assessment
based on the knowledge and information obtained [36].
This is because knowledge-based trust beliefs, such as
familiarity, allow individuals to better predict the behaviors
of trusted parties, and hence to reduce the possibility that
they may mistakenly feel that they are being unfairly taken
advantage of [31].
analysis, interpreting trust as ‘‘it is not worthwhile for the
other party to engage in opportunistic behaviors’’ and ‘‘if
the costs of being caught outweigh the benefits of cheating,
then trust is warranted since cheating is not in the best
interest of the other party’’ [10, p. 64]. Such trust is built if
an individual believes that the trusted party has nothing to
gain from being untrustworthy. Calculation-based trust is
not included in the model, because it is not appropriate for
China’s P2P context. There is no national credit system and
law enforcement is weak in China. Defaulted borrowers
may lose very little, if anything. Therefore, borrowers on
China’s P2P lending platforms do indeed have reason to
engage in opportunistic behaviors. On this basis, we
believe that lenders have no, or very low if any, calcula-
tion-based trust in borrowers on China’s P2P platforms,
and so this form of trust is excluded from the model.
Personality-based trust refers to the tendency to believe
or not in others and so to trust them [10, 24, 29]. A person
with a greater disposition to trust may tend to trust others.
Such trust belief is credit given to others before experience
can provide a more rational interpretation [10]. It is related
to an individual’s personality and is especially important in
the initial stages of a relationship [29]. Although lenders’
personalities may influence their trust in borrowers and in
online P2P intermediary, it can be cultivated neither by
borrowers nor by intermediaries. Thus, personality-based
trust is included as a control in the model.
Table 2 summarizes ten widely cited articles, which
examined specific trust beliefs as antecedents of general
trust beliefs in e-commerce contexts. The studies listed in
this table are selected from the leading IS journals,
including Information System Research, MIS Quarterly,
Journal of Management Information Systems, Omega,
Information and Management, International Journal of
Electronic Commerce, and The Journal of Strategic
Information Systems.
4.3 General trust beliefs
4.3.1 Trust in borrower
Trust in borrower is conceptualized in this study as a belief
that the borrower will act cooperatively to fulfill the len-
der’s expectations without exploiting his or her vulnera-
bilities [6]. Trust in borrower is of vital importance for
lending success. Although P2P lenders are able to select
loan requests from multiple potential borrowers, they are
often not familiar with these borrowers and repetitive
transactions between lenders and borrowers are unlikely
[42]. Therefore, the lender’s trust in the borrower is ex ante
in nature. Due to the lack of repetitive transactions, ex-ante
trust is primarily cognition-based. Such cognition-based
trust relies on rapid, cognitive cues of first impressions
[43], rather than experiential personal interactions [44].
Due to the fact that lenders’ trust in borrowers is based
on the former’s first impression of the latter, lenders often
act on information that is incomplete and far from perfect
[10]. They are thus often exposed to a high level of
uncertainty and risk in their lending decisions, especially
since the transactions are monetary in nature. Therefore,
lenders would seek to assess borrowers on a full spectrum.
There are two ways for lenders to assess borrowers. The
first is direct assessment of the information quality of loan
requests, such as reliability and the sufficiency of the
request information. The information provided in the bor-
rower’s requests may directly reflect whether he is honest
and behave professionally. The second is indirect assess-
ment. Although there are no repetitive transactions between
a particular lender and borrower, the borrower might have
already made multiple requests on the platform and inter-
acted with other lenders. These previous requests and
interactions with other lenders are the borrower’s social
capital, which may serve as a proxy for reliability and
honesty. On this basis, we include both direct assessment
(i.e. information quality) and indirect assessment (i.e.
social capital) as cognition-based trust beliefs.
Inf Technol Manag (2014) 15:239–254 243
only a buyer (i.e., the borrower) and supplier (the lender)
but also an intermediary (e.g., Prosper in the US and PPDai
in China) [10]. The lending intermediary is a platform (i.e.,
marketplace) that uses Internet structure to facilitate lend-
ing transactions among potential borrowers and lenders in
an online marketplace by collecting, processing, and dis-
seminating information [34, 45]. Lenders must put their
trust not only in borrowers but also in intermediaries. Trust
in lending intermediary is thus defined as the subjective
belief with which a lender believes that the intermediary
will institute and enforce fair rules, procedures, and out-
comes in its marketplace competently, reliably, and with
integrity, and, if necessary, will provide recourse for
lenders to deal with borrowers’ opportunistic behaviors
Similar to lender’s trust in borrowers, lender’s trust in an
intermediary is also assessed from two sources, direct and
indirect. The direct assessment is based on whether the
intermediary is safe for the transaction and whether it
provides high-quality services. Since P2P lending transac-
tions are monetary in nature and the lenders bear much
higher risk than borrowers, lenders have great need for the
intermediary to safeguard their…