Online peer-to-peer (P2P) lending has developed fast around the world in recent years; however, studies regarding gender discrimination and its rationality for developing countries are limited. Gender discrimination towards borrowers and its rationality in P2P lending in China are studied in this paper. Using data collected from PPdai.com, one of the largest P2P lending platforms in China, we found that, female borrowers are less likely to be funded than male borrowers, but their default rates are lower. Such results suggested that there is significant gender discrimination in P2P lending market in China, but such discrimination is out of prejudice rather than from rational reasoning. Eliminating such gender discrimination is not only beneficial to female borrowers, but also helpful for improving returns of lenders

Chen, Dongyu

Hao, Lou

Xu, Hong

English

AIS Electronic Library (AISeL)

Association for Information SystemsAIS Electronic Library (AISeL)WHICEB 2013 Proceedings Wuhan International Conference on e-BusinessSummer 5-25-2013Gender Discrimination towards Borrowers inOnline P2PLendingDongyu ChenSchool of Management, Fuzhou University, ChinaLou HaoCollege of Business, Ohio University, USAHong XuSchool of Management, Fuzhou University, ChinaFollow this and additional works at: http://aisel.aisnet.org/whiceb2013This material is brought to you by the Wuhan International Conference on e-Business at AIS Electronic Library (AISeL). It has been accepted forinclusion in WHICEB 2013 Proceedings by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contactelibrary@aisnet.org.Recommended CitationChen, Dongyu; Hao, Lou; and Xu, Hong, "Gender Discrimination towards Borrowers in Online P2PLending" (2013). WHICEB 2013Proceedings. 55.http://aisel.aisnet.org/whiceb2013/55The Twelfth Wuhan International Conference on E-Business——E-Business Management in Organization Track 21Gender Discrimination towards Borrowers in Online P2P LendingChen Dongyu1, Lou Hao2, Hong Xu11 School of Management, Fuzhou University, China2College of Business, Ohio University, USAAbstract：Online peer-to-peer (P2P) lending has developed fast around the world in recent years; however,studies regarding gender discrimination and its rationality for developing countries are limited. Genderdiscrimination towards borrowers and its rationality in P2P lending in China are studied in this paper. Using datacollected from PPdai.com, one of the largest P2P lending platforms in China, we found that, female borrowers areless likely to be funded than male borrowers, but their default rates are lower. Such results suggested that there issignificant gender discrimination in P2P lending market in China, but such discrimination is out of prejudicerather than from rational reasoning. Eliminating such gender discrimination is not only beneficial to femaleborrowers, but also helpful for improving returns of lenders.Keywords: online peer-to-peer lending, gender discrimination, logistic regression.1. INTRODUCTIONOnline peer-to-peer lending (P2P lending) refers to unsecured loans between lenders and borrowers throughonline platforms without the intermediation of any financial institutions [1, 2]. It is a new way to lend andborrow money through online platform. It has become popular in China. China has millions ofmicro-entrepreneurs and rural poor borrowers who may not be able to access finance from traditional sources,which makes it a big market for peer-to-peer groups. In China one of the well-known companies is Ppdai, whichwas built in 2007 and now has attracted over 500,000 customers by the end of 2012.In the online P2P lending both borrowers and lenders have to register in the platform. Borrowers could posta loan request, and then lenders could review the loan requests and determine which ones to fund. Suchlending could take place between borrowers and lenders who never know each other, so it is fast and easy tomake a deal, which attracts many low-income individuals who need a small amount of loan.In the credit lending market, female-owned small enterprises tend to be less likely to receive loans frombanks and pay higher interest rates than male-owned enterprises. In the labor market, such discrimination stillexists. Barasinska[3] proves that there are gender difference in lending behaviors in the P2P lending market.Carter et al.[4] further showed that different relative importance will be attached to loans between male andfemale lenders. Due to gender discrimination, women are less likely to access financial resources and hence bein economically disadvantaged positions in society. Such phenomenon is especially prominent in lessdeveloped countries, which presents a significant problem for anti-poverty. In order to provide necessaryfinancial aids to those in need, we should have a clear picture of what extent gender may influence theiraccessing financial resources. The emergence of P2P lending allows us to have the opportunity to empiricallyexamine this issue. Therefore, the goals of the paper are the following:(1) Examine whether there is any significant gender discrimination in seeking loans in developingcountries.(2) If such discrimination exists, whether such discrimination is rational.2. RESEARCH METHODS22 The Twelfth Wuhan International Conference on E-Business——E-Business Management in Organization TrackLogistic regression model was used to test the existence of gender discrimination. Each borrowing listing isregarded as an observation. We also use logistic regression to analyze the rationality of gender discrimination.The dependent variables defined as 1 if a loan defaults and 0 otherwise. The independent variable includes twofolds: information of borrowers and information of loans.The research data all comes from Ppdai, which is one of the leading online p2p platforms in China. Theoperation procedure of Ppdai resembles to Prosper which is the leading online p2p lending platform in US.Ppdai mainly serves low-income individuals and small business groups, including the individual small businessowners, college students and ordinary company staffs who need small amount loans and can’t get loans frombanks easily. And in the past few years Ppdai has developed more than 500,000 members.3. RESULTSOF DATAANALYSISIn order to analyze the gender difference and test the hypotheses, the results of descriptive analysis aredisplayed in table 2. As the results show, there are 20690 observed samples in the success model and 3555 inthe default model. It also reveals that there are more than 80% male borrowers, which means online P2P lendingis still a men dominant market. It is the first evidence for the gender difference in the online P2P market. Thenthere should be some disadvantages for women. The discussion will be displayed in the next section.Table 1. Descriptive analysisGender Success Default0 1 percent 0 1 percent1(men) 9278 8106 84.02 2877 89 83.432(women) 1689 1617 15.98 566 23 16.57Then, to make a better understanding of the gender difference and how the relation is, the data was fed intothe logistic regression model. The results are showed in table 3, table 4and table 5.Table 2. Test the existence of gender discriminationNote: *, ** and *** indicate the 0.10, 0.05 and 0.01 levels of significance. The dependent variable is Boolean value indicating whethera borrow listing is fully funded.As shown in table 3, the impact of gender on funding success is significant (b=-0.0916, p<0.10). ThePseudo-R2 is 12.6%, meaning a significant amount of variance is explained by independent variables. The abovefindings suggest that there is significant gender discrimination in loan seeking process, thus H1 was supported.Table 4 showed that the impact of gender on loan default is significant (b=-0.5531, p<0.05). The Pseudo-R2is 7.8%. Such results implied that after controlling the covariates, the default rate for female borrowers isParameter DF Estimate Standard Error Pr>ChiSqIntercept 1 1.6976*** 0.1368 <.0001BorrowingAmount 1 0.000032 *** 2.935E-6 <.0001Gender 1 -0.0916* 0.0506 0.0702Age 1 -0.0105*** 0.00408 0.0100Education 1 -0.1175 *** 0.0166 <.0001Marriage 1 -0.0890* 0.0469 0.0577FriendNumberPseudo-R2Number of obs.1 -0.0260***12.6%124240.000754 <.0001The Twelfth Wuhan International Conference on E-Business——E-Business Management in Organization Track 23significantly lower than their male counterpart. In contrary to our hypothesis, the female borrowers are morereliable than male borrowers. Thus H2 was rejected.Table 3. Test the rationality of gender discriminationParameter DF Estimate Standard Error Pr>ChiSqIntercept 1 2.6145*** 0.9999 0.0089BorrowingAmount 1 0.000049 0.000033 0.1409Gender 1 -0.5531 ** 0.2724 0.0423Age 1 0.0171 0.0314 0.5865Education 1 -0.2248 * 0.1155 0.0515Marriage 1 0.4786 * 0.2837 0.0916FriendNumberPseudo-R2Number of obs1 0.0220***7.8%18730.00545 <.0001Note: *, ** and *** indicate the 0.10, 0.05 and 0.01 levels of significance. The dependent variable is a Boolean valueindicating whether a loan defaults.The odds ratio estimates are shown in table 5 to have a clearer picture of how gender affects fundingsuccess and loan defaults. It showed that the funding rate is 9.8% lower for female borrowers than for maleborrowers, but the default rate is 43.5% lower for female borrowers than for male borrowers.Table 4. Odds ratio estimatesEffectPoint EstimateDefault SuccessBorrowingAmount 1.000 1.000Gender 0.575 0.912Age 1.017 0.990Education 0.799 0.889Marriage 1.614 0.915FriendNumber 1.022 0.9745. DISCUSSIONSAND IMPLICATIONSThe data of transaction about borrowers is collected from Ppdai online peer-to-peer platform. We used thelogistic regression to analyze the gender difference in borrowing rates and default rates of borrowers. Theresult of data analysis suggests the existence of gender discrimination in the online p2p lending market. Despiteof the good performance on the default rates, women still don’t get more loans.Although female borrowers are very hard to get loans in the P2P lending market, they are more reliable thanmale borrowers. The result showed that the default rate of female borrowers ismuch lower than that of maleborrowers. It means that the gender discrimination is caused mainly by prejudice rather than by rational analysis.Such discrimination is not only harmful to female borrowers in the market, but also harmful to the marketefficiency and social welfare. Lenders may wrongly pick male borrowers who are more likely to default.The reason that default rate for female borrowers is lower may be that they have less opportunities to seekloans in developing countries such as China, so they cherish any chance of getting loans. Only if femaleborrowers can keep good credit records, they can have chances to borrow again in the future. As a result, it isbeneficial for people to lend to female borrowers.24 The Twelfth Wuhan International Conference on E-Business——E-Business Management in Organization TrackSuch results entail strong managerial implications. Because of gender discrimination, some good qualityfemale borrowers who are in need of money and are credible to repay loans are not eligible to access loans. Suchdiscrimination is irrational and may cause loss of social welfare. In order to improve market efficiency, policymakers should be fully aware of the existence of gender discrimination in the lending market and providenecessary actions to eliminate such discriminations. For lending platforms, they should inform lenders thatfemale borrowers are also reliable and investing in female borrowers is beneficial.Such results also entail research implications. Although gender discrimination is a hot topic and was widelystudied in a number of fields; there have been limited studies in the field of lending market, especially fordeveloping countries. Due to the fact that financial institutions are less mature in developing countries andfemales are in a social economically disadvantaged position, providing financial services to female borrowersare especially important. This study not only confirms the existence of gender discrimination, but also exploresthe rationality behind such discriminations. The current research extends the previous research that genderdiscrimination is the result of social prejudice and could do harm not only to female borrowers, but also to thelenders themselves. Such results could enrich our understanding as to the causes of gender discrimination and itseffect. Such results may also be useful to the development of gender discrimination theories and come aboutmeasures to tackle it.6. CONCLUSIONSGender discrimination of borrowers and its rationality in P2P lending are studied in this paper. Using datacollected from PPdai.com, one of the largest P2P lending platforms in China, we found that, female borrowersare less likely to be funded than male borrowers, but their default rates are lower. Such results suggested thatthere is significant gender discrimination in P2P lending market in China, but such discrimination is out ofprejudice rather than from rational reasoning. Eliminating such gender discrimination is not only beneficial tofemale borrowers, but also helpful for improving returns of lenders.References[1] Lin, M.F., N.R. Prabhala, and S. Viswanathan. Social networks as signaling mechanisms: Evidence from onlinepeer-to-peer lending. Working Paper 2009 [cited 2011 8/15]; Available from:http://pages.stern.nyu.edu/~bakos/wise/papers/wise2009-p09_paper.pdf.[2] Collier, B. and R. Hampshire. Sending mixed signals: Multilevel reputation effects in Peer-to-Peer lending markets. inCSCW. 2010. Savannah, Georhia, USA.[3] Barasinska, N., The role of gender in lending business: Evidence from an online market for peer-to-peer lending. 2009.[4] Carter S, E.S., W. Lam and F. Wilson, Gender, entrepreneurship, and bank lending:the criteria and processes used bybank loan officers in assessing applications. Entrepreneurship: Theory and Practice, 2007. 37: p. 427-444.

Gender Discrimination towards Borrowers in Online P2PLending

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Gender Discrimination towards Borrowers in Online P2PLending

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