Study on the determinants of decision-making in peer-to-peer lending in South Korea

Kim, Dongwoo; Maeng, Kyuho; Cho, Youngsang

doi:10.1080/16081625.2018.1540939

Cited by 13 publications

(10 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several researchers have focused on determining the impact of the overall factors (Cai, Lin, Xu, & Fu, 2016;X.-h. Chen, Jin, Zhang, & Yang, 2016;Feng, Fan, & Yoon, 2015;Kgoroeadira et al, 2019). Others have focused on speci c factors such as linguistic styles (Herzenstein, Sonenshein, & Dholakia, 2011;Kim, Maeng, & Cho, 2018;Larrimore, Jiang, Larrimore, Markowitz, & Gorski, 2011), gender (Barasinska & Schafer, 2014), cultural and geographical differences (Burtch, Ghose, & Wattal, 2014), trust in borrowers or intermediaries (D. Chen et al, 2014;Wan, Chen, & Shi, 2016), punctuation used in loan descriptions (X. Chen, Huang, & Ye, 2018), appearance (Jin, Shang, & Ma, 2019), voluntary information (Han, Chen, Liu, Luo, & Fan, 2018;Michels, 2012), friendship (Liu, Brass, Lu, & Chen, 2015), and herding behavior among investors (Herzenstein, Dholakia, & Andrews, 2011;Y.…”

Section: Review Of Related Literaturementioning

confidence: 99%

“…(2019) Ma et al (2018), Malekipirbazari and Aksakalli (2015), Serrano-Cinca et al (2015) Present models that predict repayment performance with ex-post determinants Theme 3: Determinants of ex-ante funding decision-making P2P lending Cai et al (2016), X.-h. Chen et al (2016), Feng et al (2015, Kgoroeadira et al (2019) Overall factors including a borrower's demographic characteristics, loan terms, credit and financial information Herzenstein, Sonenshein, et al (2011), Kim et al (2018), Larrimore et al (2011) Linguistic styles Barasinska and Schafer (2014) Gender Burtch et al (2014) Cultural and geographical differences D. Chen et al (2014), Wan et al (2016) Trust in borrowers or intermediaries X. Chen et al (2018) Punctuation used in loan descriptions Jin et al (2019) Appearance Han et al (2018), Michels (2012) Voluntary information Liu et al (2015) Friendship , Kim (2020), Luo and Lin (2013), Yu et al (2018) Herding behavior Platform-generated, Loan-describing, Borrower-attributed II, II-1, II-2, IV, IV-1, IV-2 Repayment Platform-generated, Loan-describing, Borrower-attributed I-1-1, I-2-1, III-1-1, III-2-1 Funding Loan-describing, Borrower-attributed I-1-2, I-2-2, III-1-2, III-2-2 Funding Platform-generated, Borrower-attributed I-1-3, I-2-3, III-1-3, III-2-3 Funding Platform-generated, Loan-describing…”

Section: Categorymentioning

confidence: 99%

See 1 more Smart Citation

Can investors’ collective decision-making evolve? Evidence from Peer-to-Peer lending markets

Kim

2021

Preprint

Self Cite

View full text Add to dashboard Cite

This study tries to identify the accuracy of individual investors' capability to predict a borrower’s creditworthiness in peer-to-peer lending markets and examine whether their ability is likely to evolve over time. The results of this study show that there is no significant difference between the predictive power of investors' ex-ante funding decision model and that of the ex-post repayment model over a borrower’s repayment performance. Furthermore, the predictive power of investors' ex-ante funding decision over a borrower’s repayment performance is shown to improve over time . It is also found that the main reason why investors’ predictive power improve over time is because investors can assess more accurately the information provided by the platform operator and describe the borrower's characteristics. The results of this study are important as they confirm the possibility of optimizing and streamlining the P2P lending market, through the evolution of investors’ decision making.

show abstract

Section: Review Of Related Literaturementioning

confidence: 99%

Section: Categorymentioning

confidence: 99%

Can investors’ collective decision-making evolve? Evidence from Peer-to-Peer lending markets

Kim

2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…(2019) Ma et al (2018), Malekipirbazari and Aksakalli (2015), Serrano-Cinca et al (2015) Present models that predict repayment performance with ex-post determinants Theme 3: Determinants of ex-ante funding decision-making P2P lending Cai et al (2016), X.-h. Chen et al (2016), Feng et al (2015, Kgoroeadira et al (2019) Overall factors including a borrower's demographic characteristics, loan terms, credit and financial information Herzenstein, Sonenshein, et al (2011), Kim et al (2018), Larrimore et al (2011) Linguistic styles Barasinska and Schafer (2014) Gender Burtch et al (2014) Cultural and geographical differences D. Chen et al (2014), Wan et al (2016) Trust in borrowers or intermediaries X. Chen et al (2018) Punctuation used in loan descriptions Jin et al (2019) Appearance Han et al (2018), Michels (2012) Voluntary information Liu et al (2015) Friendship , Y. , Kim (2020), Luo and Lin (2013), Yu et al (2018) Herding behavior…”

Section: Categorymentioning

confidence: 99%

Can investors’ collective decision-making evolve? Evidence from peer-to-peer lending markets

Kim¹

2021

Electron Commer Res

Self Cite

View full text Add to dashboard Cite

This study tries to identify the accuracy of individual investors' capability to predict a borrower's creditworthiness in peer-to-peer lending markets and examine whether their ability is likely to evolve over time. The results of this study show that there is no signi cant difference between the predictive power of investors' ex-ante funding decision model and that of the ex-post repayment model over a borrower's repayment performance. Furthermore, the predictive power of investors' ex-ante funding decision over a borrower's repayment performance is shown to improve over time . It is also found that the main reason why investors' predictive power improve over time is because investors can assess more accurately the information provided by the platform operator and describe the borrower's characteristics. The results of this study are important as they con rm the possibility of optimizing and streamlining the P2P lending market, through the evolution of investors' decision making.Research question 1: How different is the predictive power on a borrower's default of the individual investors' ex-ante funding decision model from that of the ex-post repayment model? After identifying suboptimal levels of investors' ability to make collective funding decisions, this study's primary research purpose is to determine whether the quality of the decision can be improved as the market structure evolves over time. Therefore, we present a second research question as follows.Research question 2: Do investors' predictive powers improve as market structures evolve over time?In addition, it will also be important to identify what the speci c improvement factors are if investors' collective decision-making evolves. To this end, the study also seeks to further clarify what investor information is improving the judgment among the borrowers' various information. The study also presents the following research questions in relation to it.Research question 3: If investors' predictive power evolves, what is the reason for it?While the investors' ex-ante funding decision primarily determines whether the funding is approved or not, the fundamental criterion for investors' decisionmaking is whether or not the borrower will repay the money loaned on time (

show abstract

“…While D. Chen et al (2017) argued that female borrowers were more likely to be funded than male borrowers in China, Kuwabara and Thebaud (2017) found that female borrowers seeking loans for business purposes were less likely to receive funding on Prosper in the U.S. In Korea, Kim, Maeng, and Cho (2018) found that female borrowers have a higher probability of loan success than males using data from Moneyauction. Several studies have shown that gender discrimination is not linked to funding success.…”

Section: Literature Reviewmentioning

confidence: 99%

Sexism and Ageism in a P2P Lending Market: Evidence from Korea

KIM¹

2020

JAFEB

Self Cite

View full text Add to dashboard Cite

This study attempts to identify gender and age discrimination by individual lenders in P2P lending markets by analyzing empirical transaction data from multiple platforms including Moneyauction, Popfunding, and 8percent. To do this, the study investigates the effects and importance of a borrower's gender and age on individual lenders' preferences and a borrower's actual repayment performance using multiple linear regression and relative weight analyses. As a result, no gender discrimination is found in the three Korean P2P lending markets, and such indiscrimination is rational, on the grounds that the borrower's gender does not have a statistically significant impact on the lenders' preferences as well as his/her actual repayment performance, and its relative importance is minimal. While, there marginally exists age discrimination against a borrower in the markets, and such ageism is likely to be irrational, on the grounds that the borrower's age has a partly significant and minimally important impact on the lenders' preferences, but has no significant and important impact on his/her repayment performance. For the first time, these findings help to clarify gender and age discrimination issues in the P2P lending market by identifying the rationality of individual lenders' preferences to the borrower's gender and age in the Korea.

show abstract

Study on the determinants of decision-making in peer-to-peer lending in South Korea

Cited by 13 publications

References 17 publications

Can investors’ collective decision-making evolve? Evidence from Peer-to-Peer lending markets

Can investors’ collective decision-making evolve? Evidence from Peer-to-Peer lending markets

Can investors’ collective decision-making evolve? Evidence from peer-to-peer lending markets

Sexism and Ageism in a P2P Lending Market: Evidence from Korea

Contact Info

Product

Resources

About