P2P&nbsp;lending&nbsp;platforms in Malaysia: What&nbsp;do&nbsp;we&nbsp;know?

Lan Thi Phuong Nguyen; Wisdom Kalabeke; Saravanan Muthaiyah; Ming Yu Cheng; Kwan Jing Hui; Hazik Mohamed

doi:10.12688/f1000research.73410.1

Home Browse P2Plendingplatforms in Malaysia: Whatdoweknow?

ALL Metrics

Views

Downloads

Get PDF

Get XML

Export

▬

✚

Research Article

P2P lending platforms in Malaysia: What do we know?

[version 1; peer review: 2 approved with reservations]

Lan Thi Phuong Nguyen ¹, Wisdom Kalabeke¹, Saravanan Muthaiyah¹, Ming Yu Cheng², Kwan Jing Hui¹, Hazik Mohamed³

Lan Thi Phuong Nguyen ¹, Wisdom Kalabeke¹, [...] Saravanan Muthaiyah¹, Ming Yu Cheng², Kwan Jing Hui¹, Hazik Mohamed³

PUBLISHED 26 Oct 2021

Author details Author details

¹ FACULTY OF MANAGEMENT, MULTIMEDIA UNIVERSITY, CYBERJAYA, SELANGOR, 63100, Malaysia
² Faculty of Accountancy and Management, Universiti Tunku Abdul Rahman, Bandar Sungai Long Cheras, Kajang, Selangor, 43000, Malaysia
³ Stella Consulting, Stella Consulting, 60 Paya Lebar Square #07-44,, 409051, Singapore

Lan Thi Phuong Nguyen
Roles: Conceptualization, Formal Analysis, Investigation, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

Wisdom Kalabeke
Roles: Data Curation, Investigation, Methodology, Validation

Saravanan Muthaiyah
Roles: Formal Analysis, Investigation, Validation

Ming Yu Cheng
Roles: Formal Analysis, Project Administration, Writing – Review & Editing

Kwan Jing Hui
Roles: Project Administration, Resources

Hazik Mohamed
Roles: Resources, Supervision, Validation

OPEN PEER REVIEW

REVIEWER STATUS

This article is included in the Research Synergy Foundation gateway.

Abstract

Background - With the recent evolution of Financial Technology (FinTech), 11 peers to peer (P2P) lending platforms have been regulated by the Securities Commission in Malaysia since 2016. P2P lending platforms offer new investment opportunities to individual investors to earn higher rates on return than what traditional lenders usually provide. However, individual investors may face higher potential risks of default from their borrowers. Therefore, individual investors need to understand the potential exposure to such P2P lending platforms to make an effective investment decision. This study aims to explore the potential risk exposures that individual investors may experience at Malaysia's licensed P2P lending platforms.
Methods - Based on data collected manually from nine P2P lending platforms over five months, relationships between interest rates and various risk classifying factors such as credit rating, industry, business stage, loan purpose, and loan duration are examined.
Results- This study shows that loans with a similar credit rating and with or without similar loan purpose; and a business stage may offer investors significantly different interest rates. In addition, loans with shorter durations may provide investors with higher interest rates than those with longer durations. Finally, loans issued by companies from the same industry appeared to be charged with similar interest. These findings are valuable to investors to prepare themselves before making their investments at the P2P lending platforms.
Conclusion- With first hand-collected data, this study provides an original insight into Malaysia's current P2P lending platforms. Findings obtained for relationships between interest rates and risk classifying factors such as credit rating, industry, business stage, loan purpose and loan duration are valuable to investors of Malaysian P2P lending platforms.

Keywords

P2P lending platforms, default risk, SMEs, individual investors, credit rating, FinTech platforms

Corresponding author: Lan Thi Phuong Nguyen

Competing interests: No competing interests were disclosed.

Grant information: The Ministry of Education of Malaysia supported this work under the 2020-FRGS project (ID: FRGS/1/2020/SS01/MMU/02/17)
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2021 Nguyen LTP et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Nguyen LTP, Kalabeke W, Muthaiyah S et al. P2P lending platforms in Malaysia: What do we know? [version 1; peer review: 2 approved with reservations]. F1000Research 2021, 10:1088 (https://doi.org/10.12688/f1000research.73410.1) First published: 26 Oct 2021, 10:1088 (https://doi.org/10.12688/f1000research.73410.1) Latest published: 14 Apr 2023, 10:1088 (https://doi.org/10.12688/f1000research.73410.3)

Introduction

As the most prominent sector in Financial Technology (FinTech), peer-to-peer (P2P) lending platforms use digital communication technology to connect lenders and borrowers online. FinTech platforms like P2P lending are easily accessed by smartphones and the internet for getting unconventional loans. Unlike traditional banks, these lending platforms do not require collateral, the ownership of a bank account, and a business plan. Borrowers are rated and categorized based on their risk profile determined by their provided personal information, including information from their social media sites.

Since the first two P2P lending platforms, named “Zopa” and “Prosper”, were launched in the U.K. and U.S. in 2005 and 2006, respectively, the P2P lending industry has grown and reached Asia. The credit crunch experienced by many traditional banks in the U.S. because of the 2008 Global Financial Crisis, forced many borrowers to turn to P2P lending platforms for their short-term financing needs. Business Wire (2020) reported that the annual compounded growth rate of the global peer to peer (P2P) lending market was around 25% between 2014 and 2019. Although there has been a slowdown in FinTech investments across America and Europe since 2016, the number of P2P lending platforms continues to increase in many emerging markets in the past few years (Stern, Makinen, and Qian, 2017).

Since 2016, 11 peer-to-peer (P2P) lending platforms have been granted licenses by the Securities Commission in Malaysia. Since then, the industry has experienced healthy growth in its first two and a half years of operation, as reported by Zhe (2019). Within the first nine months of operation, RM521.7 million were raised by the first six licensed P2P lending platforms to fund 1,560 small and medium enterprises (SMEs). By the end of 2019, the numbers of registered investors at the three most active platforms, Funding Societies Malaysia, Fundaztic and B2B FinPal, were 3,500, 1,700, and 1,500, respectively.

Kok (2021) reposted that many P2P lending platforms, i.e., Funding Societies Malaysia and Fundaztic, experienced steady growth in 2020 despite the Covid-19 pandemic. Their default rates were reported to be reasonably low at 3% and 2.5% per annum by Funding Societies and Fundaztic, respectively. There are two main reasons for this strong growth of P2P lending platforms: the cut in interest rates by Bank Negara Malaysia from 3% to 1.75% between December 2019 and July 2020, and the growth in the use of digital space during the pandemic. Thus, P2P lending platforms appear to be attractive alternative investment platforms as they offer much higher interest rates, ranging from 6% to 21% per annum across the eleven platforms.

Unlike P2P lending platforms in the West, P2P lending platforms in Malaysia are designed to give out loans only to businesses and not individual borrowers. For SMEs that cannot provide sound evidence on their business performance and enough collateral, P2P lending platforms are their best financing alternatives. However, this could imply a possibly higher rate of default faced by the P2P lending industry in Malaysia than traditional lending institutions. Therefore, investors are often advised to diversify their funds across different investment notes while investing at each platform. However, having an effective diversification strategy depends heavily on two critical elements: (1) whether investors have basic financial literacy and (2) how much information of each investment note is made known to investors by each P2P platform.

When it comes to evaluating the default risk of a borrower, information that can help arrive at one's estimated credit score is needed. For P2P lending platforms, the borrowers' credit score is based solely on information supplied by the borrower (Li, 2018). Since the information provided by P2P lending platforms are limited and not guaranteed, it would be even more challenging for investors with good financial literacy to reach a sound investment decision. Therefore, individual investors need to understand the potential exposure to such P2P lending platforms to be able to make an effective investment decision. This study explores potential exposures that individual investors may experience at licensed P2P lending platforms in Malaysia.

Methods

Individual investors would mainly like to subscribe to platforms with affordable subscription fees. Of 11 licensed P2P lending platforms in Malaysia, only 10 platforms (Funding Societies, B2B FinPal, Fundaztic, QuicKash, AlixCo, Nusa Kapital, CapSphere, MicroLEAP, Cofundr, and Money Save) require affordable initial deposits, ranging from RM5 to RM1,000, from individual investors. CapBay was excluded from this study as it requires the highest amount of initial deposit (RM10,000) from its investors. Additionally, Funding Societies was also not considered due to the complexity of its subscription. Therefore, the final sample size was nine P2P lending platforms (B2B, Fundaztic, QuicKash, AlixCo, Nusa Kapital, CapSphere, MicroLEAP, Cofundr, and Money Save).

All available information was obtained from the nine platforms for comparative analysis (Underlying data) (Nguyen, 2021). The data collection period was from January to May 2021. Data collection was done manually as a loan campaign is only announced to investors for a maximum of seven days at each platform. Once a campaign is bided on successfully, the issue note will be taken down, and its record will no longer be visible to investors who did not invest in that note.

The lender decides whom to grant the loan primarily based on the interest rate. The percentage of the interest rate is mainly dependent on the borrower’s credit score, which is based on various loan characteristics such as the type of business, business cycle, loan purpose, loan duration, and loan amount. Therefore, understanding the relationship between the prime factor - interest rate and other secondary factors such as credit score, loan term, loan duration, loan purpose, business cycle and industry will help investors to be more aware of what to expect when making their investment decisions at those platforms.

Statistical analysis

Since there is no data publicly available for individual P2P lending platforms in Malaysia, this study employs first hand-collected information for the analysis. Descriptive and cross-tabulation statistics were produced by Microsoft Excel 2010 and IBM SPSS Statistics 26, using a five-month data set to examine the potential exposure that individual investors may face at the nine selected P2P lending platforms. In addition, other tests for normality, coefficients, and multiple regression tests were also conducted. However, only descriptive statistics are reported in this paper.

Results/discussion

After the collapse of hundreds of P2P lending platforms in China since 2013 (Bloomberg Businessweek, October 3, 2018) due to fraudulent activities, P2P lending in Malaysia was somewhat restrictive until 2016. Malaysia is the first country in Southeast Asia to regulate its first six P2P market operators in 2016 (The Securities Commission, 2017). The Securities Commission of Malaysia (SC) requires that P2P lending platforms operating in Malaysia have a minimum paid capital of RM5million, assess and monitor the risk level of each prospective borrower, set limits and obligations, and ensure both issuers and lenders comply with relevant guidelines. SC further established that issuers must be sole proprietorship, partnership, limited liability companies, private unlimited and unlisted companies incorporated in Malaysia. Investors could be any individual or institution outside or within Malaysia, however, depending on rules set by an operator.

Subscription requirements at P2P lending platforms

As shown in Table 1, information required from potential investors at the nine P2P lending platforms were varied. At each P2P lending platform, potential investors must have initial deposit amounts ranging from RM5 to RM1,000, kept at a specified third-party's account at each platform. Each platform requires each investor to provide basic personal information such as identification card (ID)/passport number, most recent bank account statement, details of sources of income and proof of current residential address. Some P2P lending platforms, such as QuicKash, Money Save, and AlixCo, require additional documents: a selfie photo or a video clip that clearly shows the face of the potential investor while holding his/her passport/ID with the first page open. Most of the platforms allow only Malaysian investors, except QuicKash, MicroLEAP, CapSphere, and AlixCo. Funding Societies, in particular, welcomes investors from four countries, namely Thailand, Indonesia, Singapore, and Malaysia for investment opportunities. Nusa Kapital specifically welcomes Malaysian Muslim investors to participate. Money Save is the only platform that assesses potential investors' financial literacy to categorize them into three groups of investors: (1) with basic investment knowledge, (2) with basic investment knowledge and experience, and (3) with sophisticated investment knowledge and experience.

Table 1. Required documents for investors at nine P2P lending platforms in Malaysia.

P2P platforms	Selfie photo/video with face and IC/passport	IC/passport	Bank statement	Utility Bill	Malaysian citizens	Muslim are encouraged	Foreigners	Source of income	Assessment of financial literacy
B2B	No	Yes	Yes	Yes	Yes	No	No	Yes	No
AlixCo	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	No
Cofundr	No	Yes	Yes	No	No	No	No	Yes	No
Nusa Kapital	No	Yes	Yes	Yes	Yes	No	Yes	Yes	No
CapSphere	No	Yes	Yes	No	Yes	No	No	Yes	No
MicroLeap	No	Yes	Yes	No	Yes	No	Yes	Yes	No
Money Save	Yes	Yes	Yes	No	Yes	No	No	Yes	Yes
Fundaztic	No	Yes	Yes	No	Yes	No	No	Yes	No
QuicKash	Yes	Yes	Yes	No	Yes	No	Yes	Yes	No

Credit rating and interest rate

Credit rating is one of the most important criteria for most lending institutions, including P2P lending platforms, when deciding on the interest rate that should be charged to a borrower. A credit rating is given to a borrower based on evaluating the potential default incurred by that borrower. In Malaysia, credit ratings can be obtained from Credit Bureau Malaysia. Upon request from a lending institution, Credit Bureau Malaysia provides information such as personal identifying data, personal credit histories reported by various lenders previously, information showing the honesty and stability of a borrower, and the number of requests made by lenders and legal authorities on the borrower's credit status. Credit scores are determined based on factors that differentiate between a good and a bad borrower. A borrower with a good credit rating score can be offered lower interest rates.

However, it is found that some P2P lending platforms in Malaysia use the scores provided by Credit Bureau Malaysia, while others use their own formula to determine the scores for their borrowers. Additionally, the credit ratings are not shared between P2P lending platforms, which leads to varying credit scores across all platforms. It is unknown to investors how these scores are decided, as a result, a borrower may get a low credit score from one P2P lending platform and a higher from another.

As shown in Figure 1, the principle that loans issued by SMEs with higher credit ratings should be charged with lower interest rates does not hold for most P2P lending platforms, except for MicroLEAP.

Figure 1. Interest rates and credit ratings at nine P2P lending platforms.

The results show that some loans issued by SMEs with lower credit ratings were charged with lower interest rates. For instance, at B2B a loan issued by an SME with a lower credit rating (C), was charged with an interest rate of 12% per annum. In comparison, A was charged with a higher interest rate of 12.5% per annum for a loan issued by an SME with a higher credit rating (Figure 1). Similarly, at AlixCo platform, a loan issued by an SME with a credit rating of CAA2 (Very high credit risk) (see rating classification at https:/www.alixco.com/fag/statistics) was charged with an interest rate of 14.28% per annum, which is lower than what was (15% per annum) charged for loans issued by SMEs with CAA and CAA3. At Money Save platform, loans issued by SMEs with credit rating A were charged with interest rates ranging from 12% to 14.5% per annum, while loans issued by SMEs with credit rating B were charged with a much lower range of interest rates, i.e., 9.75% - 10.75% per annum.

Similarly, at QuicKash platform, an interest rate of 12% per annum was charged to SMEs with credit ratings ranging from 7-Good to 9-Strong. For Cofundr platform, a loan issued by an SME with a credit rating of CR3-Good was charged with a higher interest rate (9.75% per annum) as compared to that (9.6% per annum) charged to a loan issued by an SME with a lower credit rating (CR4-Satisfactory). Similarly, at CapSphere, loans issued by SMEs with a credit rating D were charged with lower interest rates (7.1%, 8% and 8.8%) as compared to those (9% and 11% per annum) charged to loans issued by SMEs with a credit rating C. Also, at Nusa Kapital platform, an interest rate of 15% per annum was charged to loans issued by SMEs with different credit ratings.

The above findings show that loans with similar credit ratings may offer investors very different interest rates. This result implies that a loan issued by a borrower with a higher credit rating can offer the same or higher interest rate charged to a loan issued by a borrower with a lower credit rating.

Interest rate and loan purpose

Loan purpose is the main reason for a borrower to request a loan. Lending institutions often assess a borrower's loan purpose to see the level of default risk associated with the requested loan. Regularly stated loan purposes declared at the nine P2P lending platforms are invoice financing, working capital, Covid-19 relief financing, trading, expansion, insurance premium, and equipment maintenance (Figure 2). As shown in Figure 2 there appears to be no specific interest rate applied to a particular loan purpose at the nine individual platforms. This result may suggest that loan purpose may not be one of the main criteria for a P2P lending platform for determining an interest rate for a borrower. This finding could be due to the similar risk level associated with the previously mentioned loan purposes.

Figure 2. Interest rates and loan purposes at nine P2P lending platforms.

These results show that loans with a similar loan purpose may offer investors significantly different interest rates. In addition, loans with different borrowing purposes can be charged with the same interest rate, suggesting that loan purposes may not indicate much difference in potential risks associated with them at the nine P2P lending platforms.

Interest rate and loan duration

Duration measures the sensitivity of the value of a debt instrument when the interest rate changes. According to the term structure of interest rates, loans with a longer duration should be charged with a higher interest rate due to the high possibility that interest rates may change during that long period.

However, this does not seem to be the case for the nine P2P lending platforms. As shown in Figure 3, a similar interest rate was applied to loans with different maturities at the nine P2P lending platforms. At B2B FinPal, loans with short durations, i.e., 37 days, had a higher interest rate than those charged for loans with a 98-day duration. Similarly, at Fundaztic, loans with a three-month duration are charged an interest rate of 15%, while a loan with a 36-month duration is charged with a lower interest rate, i.e., 12.23%. At AlixCo, the highest interest rate (15.36%) is charged to a three-month loan, while other loans with four- and six-month durations are only charged at 15%. At MicroLEAP, a 12-month loan is charged with a higher interest rate (14%) than those (12%, 11.5% and 11%) charged to 24-, 30- and 36-month loans. At Money Save, six 1-month loans offer investors interest rates of either 14.75% or 12%, while a six-month loan offers investors a 10.75% interest rate.

Figure 3. Interest rates and loan durations at nine P2P lending platforms.

At Cofundr, a one-month loan is charged with the highest interest rate of 17.5%. At CapSphere, some 12-month loans are charged with lower interest rates (8.8% per annum) than those (10% per annum) charged to six-month loans. At NursaKapital, a three-month loan is also charged with a higher interest rate (15%) than that (14%) charged to a six-month loan.

These results show that loans with a shorter duration may offer investors higher interest rates than loans with longer durations. This suggests that individual investors can look for loans with a duration of one month and still earn an interest rate that is much higher than the one offered by a 12-month loan at the nine P2P lending platforms.

Interest rates and business cycles

Most companies asking for loans at the nine P2P lending platforms are in one of the three main stages: growth, extension, and maturity. A stage that a business is going through may indicate the uncertainties that it may face. In a typical business cycle, a company goes through seven stages: seed, startup, growth, established, extension, decline, and exit. There are plenty of opportunities for growing companies; however, they may be exposed to high competition, unstable economy, and market demand, which may hamper their business. Thus, it is also a concern for lenders when granting loans to such businesses. They aim to expand the market share and achieve a new profit level for companies in their extension stages. However, if the expansion to a new product line adds considerable risk to a firm, lenders may need to evaluate loan purposes for such businesses. At a mature/decline stage, companies can experience a drop in their revenues and profits, and therefore might want to close their business. It is due to this reason that lenders find granting loans to these businesses a high risk.

As shown in Figure 4, most loans given by the nine P2P lending platforms are for companies in their growth and expansion stages. However, mixed interest rates are charged to both growing and expanding companies at most platforms, except Nusa Kapital. This finding may be mainly due to the limited data available on Nusa Kapital. The stage of a business does not reflect its entire potential risk. A similar interest rate may be charged to both growing and expanding companies on the same platform. In eight out of nine P2P lending platforms, fewer loans are given to mature businesses. There are two possible reasons for this: (1) mature businesses can get loans at traditional lending institutions at lower rates, (2) P2P lending platforms may view small mature businesses much riskier than growing and expanding businesses due to their potential closure.

Figure 4. Interest rates and stages of business at nine P2P lending platforms.

In short, loans issued by companies are primarily in their growth and expansion stages. It is shown that similar interest rates may be charged to loans issued by companies at different business stages. Moreover, there is no specific range of interest rates applied to loans issued by companies at the same business stage, from the same platform. In other words, the business stage may not be an essential factor in evaluating risks by the nine P2P lending platforms.

Interest rate and industry

If an industry is less sensitive to any economic downturns, companies from that industry are often expected to have stable businesses for a long time. Thus, lending institutions may prefer to provide loans for such businesses.

The ununiformed classification of industries in the nine P2P lending platforms, as shown in Figure 5, may indicate potential different risk assessments done by each platform for businesses applying for loans. The results show that at B2B the industries with two or more loans charged with a similar interest rate are: advertising (2), consumer goods (3), design (2), import and export (3), and E-commerce (2). In contrast, loans from the same industry, i.e., construction, food and beverages, packaging and distribution, and trading, can be charged with different interest rates. For AlixCo, loans that come from two classified industries: Retail/Trade (FMCG) (4) and Retail/Trade (Smartphone) (18), are charged at the same interest rates, 14.28% and 15.2%, respectively. However, loans from the E-commerce industry are charged with different interest rates, ranging from 13.8% to 15.1%. For MicroLEAP, two loans from the automobile industry are charged at the same interest rate (12%), while loans from the E-commerce industry are charged with different interest rates, ranging from 11.5% to 14%. For Money Save, it appears that loans from the same industries are charged with different interest rates. For QuicKash, only loans from E-commerce are charged at the same rate of 8% per annum. However, it cannot be determined if all future loans from E-commerce will be charged at the rate of 8% since only two loans were reported for this industry at the time of data collection. For Cofundr, loans from Automobile are charged with the same interest rate of 15%. However, there were only two loans reported for this industry.

Figure 5. Interest rates and industries at nine P2P lending platforms.

For CapSphere, three different loans from Freight and Logistics are charged at the same interest rate of 7.1%, while loans from other industries are charged at various interest rates. Due to limited data on Fundaztic and Nursa Kapital, a conclusion cannot be reached for these two P2P lending platforms.

In short, there seems to be a pattern of having loans issued by companies from the same industry being charged with similar interest rates across the nine P2P lending platforms. Thus, investors may select loans issued by companies from industries that often offer higher interest rates to improve their income streams.

Study limitation

This study provides a first and original insight into the current P2P lending platforms in Malaysia. However, the analysis was based on a small sample size as it only considered nine P2P lending platforms in this country.

Conclusion

• Loans with similar credit ratings may offer investors significantly different interest rates.
• Loans with similar purposes may offer investors different interest rates.
• Loans with shorter durations may offer investors higher interest rates as compared to those with longer durations.
• No specific range of interest rates was applied to loans issued by companies at the same business cycle.
• Loans issued by companies from the same industry appeared to be charged with similar interest.

The five-month collected data in this study provides a first and original insight into Malaysia's current P2P lending platforms, which will be valuable to potential investors to prepare themselves before making their investments at those platforms.

Data availability

Underlying data

Figshare: P2P Lending Platforms in Malaysia: What Do

We Know?

Doi: 10.6084/m9.figshare.14880369 (Nguyen, 2021).

This project contains the following underlying data:

Data file 1. Dataset_P2P lending in Malaysia What do we know_TIM21109.xlsx

Data are available under the terms of the Creative Commons International “No rights reserved” data waiver (CC BY 4.0).

Ethical approval

The Research Ethics Committee of Multimedia University approved this research to be conducted. The reference number of this approval is: TTO/REC/EA/123/2021.

Author contributions

All authors contribute to the data collection. The literature review, research framework and data analysis have been conducted by Nguyen Thi Phuong Lan, Wisdom Kalabeki, and Saravanan Muthaiyah. Cheng-Ming Yu evaluated the findings and discussion of the analysis. Hazik Mohamed gave comments on the practical contribution of this project. Kwan Jing Hui assisted with the data subscription.

Acknowledgement

We acknowledge the valuable feedback received from the Managing Director of Stella Consulting Group through our project. We also acknowledge the collaborations between researchers from MMU, UPM and UTAR, that allowed the funding application for this project to be successfully approved by the Ministry of Education of Malaysia. We also acknowledge the work contributed by all researchers in this project.

References

Bloomberg News: How China’s Peer-to-Peer Lending Crash Is Destroying Lives.2018.Reference Source
Business Wire: Global Peer to Peer (P2P) Lending Market Trends, Growth, Opportunity Report 2020-2025 - ResearchAndMarkets.com.2020 December 15, 2020.
Chen X, Chong Z, Giudici P, et al.: Networking with Peers: Evidence from a P2P Lending Platform. Asian Development Bank Institute, Working Paper No.1080, February 2020.2020.
Gibilara L, Mattarocci G: Peer-to-Peer lending and real estate mortgages: Evidence from the United Kingdom. J. Euro. Real Estate Res. 2018; 11(3): 319–334. Publisher Full Text
Gonsalez L: Blockchain, herding and trust in peer-to-peer lending. Manag. Finance 2019; 46: 815–831. Publisher Full Text
He Q, Li X: The Failure of Chinese Peer-to-Peer Lending Platforms: Finance and Politics. J. Corp. Finan. 2021; 66: 101852. Publisher Full Text
Hidajat T: Unethical practices peer-to-peer lending in Indonesia. J. Finan. Crime. 2020; 27(1): 274–282. Publisher Full Text
Kim D: Bounded rationality in a P2P lending market. Review of Behavioral Finance. 2020; 13: 184–201. Publisher Full Text
Kok C: Asset Quality of P2P Players Remain inact. Star. 2021.May 22 2021.Reference Source
Li Q: the Mechanism and Effectiveness of Credit Scoring of P2P Lending Platform: Evidence from Renrendai.com. China Finance Review International. 2018; 8(3): 256–274. Publisher Full Text
Lusardi A, Mitchell OS: Planning and Financial Literacy: How Do Women Fare?. Am. Econ. Rev. 2008; 98: 413–417. Publisher Full Text
Nemoto N, Storey D, Huang B: Optimal Regulation of P2P Lending for Small and Medium-Sized Enterprises. Asian Development Bank Institute, Working Paper No. 912.2019.
Nguyen TPL: Data Source_P2P Lending Platforms in Malaysia: What Do We Know? figshare. Dataset. 2021. Publisher Full Text
Rosavina M, Rahadi RA, Kitri ML, et al.: P2P lending adoption by SMEs in Indonesia. Qualitative Research in Financial Markets. 2019; 11(2): 260–279. Publisher Full Text
San-Jose L, Retolaza JL: Crowdlending as a socially innovative corporate financial instrument. Int. Perspectives on Crowdfunding. 2017; 129–149.
Shi X, Wu J, Hollingsworth J: How does P2P lending platform reputation affect lenders ‘decision in China?. Int. J. Bank Mark. 2019; 37(7): 1566–1589. Publisher Full Text
Stern C, Makinen M, Qian Z: FinTechs in China – with a special focus on peer-to-peer lending. J. Chinese Economic and Foreign Trade Studies. 2017; 10(3): 215–228. Publisher Full Text
Trönnberg CC, Hemlin S: Lending decision making in banks: A critical incident study of loan officers. Eur. Manag. J. 2014; 32(2): 362–372. Publisher Full Text
The World Bank Group: The little data book on Financial Inclusion. The Global Findex database.2017.Reference Source
Zhe KSK: P2P Financing Industry Growing. the Edge Malaysia. 2019.December 26, 2019.Reference Source

Comments on this article Comments (0)

Version 3

VERSION 3 PUBLISHED 26 Oct 2021

Author details Author details

Lan Thi Phuong Nguyen
Roles: Conceptualization, Formal Analysis, Investigation, Methodology, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

Wisdom Kalabeke
Roles: Data Curation, Investigation, Methodology, Validation

Saravanan Muthaiyah
Roles: Formal Analysis, Investigation, Validation

Ming Yu Cheng
Roles: Formal Analysis, Project Administration, Writing – Review & Editing

Kwan Jing Hui
Roles: Project Administration, Resources

Hazik Mohamed
Roles: Resources, Supervision, Validation

Competing interests

No competing interests were disclosed.

Grant information

The Ministry of Education of Malaysia supported this work under the 2020-FRGS project (ID: FRGS/1/2020/SS01/MMU/02/17)
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Article Versions (3)

version 3

Revised

Published: 14 Apr 2023, 10:1088

https://doi.org/10.12688/f1000research.73410.3

version 2

Revised

Published: 04 Apr 2022, 10:1088

https://doi.org/10.12688/f1000research.73410.2

version 1

Published: 26 Oct 2021, 10:1088

https://doi.org/10.12688/f1000research.73410.1

© 2021 Nguyen LTP et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Download

Export To

metrics

	Views	Downloads
F1000Research	-	-
PubMed Central Data from PMC are received and updated monthly.	-	-

Citations

SEE MORE DETAILS

CITE

how to cite this article

Nguyen LTP, Kalabeke W, Muthaiyah S et al. P2P lending platforms in Malaysia: What do we know? [version 1; peer review: 2 approved with reservations]. F1000Research 2021, 10:1088 (https://doi.org/10.12688/f1000research.73410.1)

NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article.

track

receive updates on this article

Track an article to receive email alerts on any updates to this article.

Open Peer Review

Version 1

VERSION 1

PUBLISHED 26 Oct 2021

Views

Reviewer Report 04 Mar 2022

Ryan Randy Suryono, Faculty of Engineering and Computer Science, Universitas Teknokrat Indonesia, Kota Bandar Lampung, Indonesia

Approved with Reservations

https://doi.org/10.5256/f1000research.77058.r126134

This study explores potential exposures that individual investors may experience at licensed P2P lending platforms in Malaysia.

1. In the introduction, it is necessary to explain the reason for the the research. Why was this research was conducted? Why Malaysia? This section has very few references.

2. The methodology section should be explained step by step. What is the process for determining the feasibility of a case study? What is the process of data collection and analysis until it becomes the research result?

3. The results section should produce an in-depth discussion. How are lessons learned from the findings? Do the results support other research? What are the theoretical and practical implications? Can the author also compare P2P Lending practices in other countries? It might be an interesting review if there are some benchmarks.

4. Overall, this article needs a lot of improvement in substance by enriching the study literature. Please correct the citation and proofread.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

References

1. Suryono R, Purwandari B, Budi I: Peer to Peer (P2P) Lending Problems and Potential Solutions: A Systematic Literature Review. Procedia Computer Science. 2019; 161: 204-214 Publisher Full Text
2. Suryono R, Budi I, Purwandari B: Challenges and Trends of Financial Technology (Fintech): A Systematic Literature Review. Information. 2020; 11 (12). Publisher Full Text

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Fintech; P2P Lending

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

CITE

Report a concern

Author Response 04 Apr 2022

Thi Phuong Lan Nguyen, FACULTY OF MANAGEMENT, MULTIMEDIA UNIVERSITY, CYBERJAYA, 63100, Malaysia

04 Apr 2022

Author Response

Dear Prof. Dr. Ryan Randy Suryono,

First of all, we would like to express our sincere thanks and gratitude for being one of the reviewers for our research paper.
... Continue reading Dear Prof. Dr. Ryan Randy Suryono,

First of all, we would like to express our sincere thanks and gratitude for being one of the reviewers for our research paper.

Upon receiving all your constructed comments, we have revised and made corrections accordingly.

The following are our responses to your given comments:

1. For the comment #1: In the introduction, it is necessary to explain the reason for the research. Why was this research was conducted? Why Malaysia? This section has very few references.

We have added the justification for the study as suggested (see Page 3).

We have also added a section of literature review to show the related works and the gap in literature the study aims to fill in (see Page 3).

2. For the comment #2: The methodology section should be explained step by step. What is the process for determining the feasibility of a case study? What is the process of data collection and analysis until it becomes the research result?

We have added details of the sample of loan campaigns recorded from the nine P2P lending platforms (page 8).

The following table is added:

Table 1: Number of Loan Campaigns Recorded from January to May 2021 at the Nine Malaysian P2P Lending Platforms (Page 9)

We have also explained the analysis method used for the study (Page 8).

3. For the comment #3: The results section should produce an in-depth discussion. How are lessons learned from the findings? Do the results support other research? What are the theoretical and practical implications? Can the author also compare P2P Lending practices in other countries? It might be an interesting review if there are some benchmarks.

We have added more interpretation of the results, linked them to past studies and practices, and provided implications and suggestions to each finding section. (see Page 9 - Page 14)

4. For the comment #4: Overall, this article needs a lot of improvement in substance by enriching the study literature. Please correct the citation and proofread.

We have also added a section of literature review to show the related works and the gap in literature the study aims to fill in (see Page 3).

We have added more references and corrected citations as suggested.

The article has gone through a few rounds of proofreading. (see page 15 – 16)

We are looking forward to having further feedback and approval.

Many thanks,

On behalf of the team,

Lan Nguyen (Ph.D.)
Dear Prof. Dr. Ryan Randy Suryono,

First of all, we would like to express our sincere thanks and gratitude for being one of the reviewers for our research paper.

Upon receiving all your constructed comments, we have revised and made corrections accordingly.

The following are our responses to your given comments:

1. For the comment #1: In the introduction, it is necessary to explain the reason for the research. Why was this research was conducted? Why Malaysia? This section has very few references.

We have added the justification for the study as suggested (see Page 3).

We have also added a section of literature review to show the related works and the gap in literature the study aims to fill in (see Page 3).

2. For the comment #2: The methodology section should be explained step by step. What is the process for determining the feasibility of a case study? What is the process of data collection and analysis until it becomes the research result?

We have added details of the sample of loan campaigns recorded from the nine P2P lending platforms (page 8).

The following table is added:

Table 1: Number of Loan Campaigns Recorded from January to May 2021 at the Nine Malaysian P2P Lending Platforms (Page 9)

We have also explained the analysis method used for the study (Page 8).

3. For the comment #3: The results section should produce an in-depth discussion. How are lessons learned from the findings? Do the results support other research? What are the theoretical and practical implications? Can the author also compare P2P Lending practices in other countries? It might be an interesting review if there are some benchmarks.

We have added more interpretation of the results, linked them to past studies and practices, and provided implications and suggestions to each finding section. (see Page 9 - Page 14)

4. For the comment #4: Overall, this article needs a lot of improvement in substance by enriching the study literature. Please correct the citation and proofread.

We have also added a section of literature review to show the related works and the gap in literature the study aims to fill in (see Page 3).

We have added more references and corrected citations as suggested.

The article has gone through a few rounds of proofreading. (see page 15 – 16)

We are looking forward to having further feedback and approval.

Many thanks,

On behalf of the team,

Lan Nguyen (Ph.D.)
Competing Interests: No competing interests from us. Close
Report a concern
Reviewer Response 11 Apr 2022

Ryan Randy Suryono, Faculty of Engineering and Computer Science, Universitas Teknokrat Indonesia, Kota Bandar Lampung, Indonesia

11 Apr 2022

Reviewer Response

All suggestions for revision have been done well. Authors have added more interpretations of the results, linked them to previous studies and practice, and provided implications and suggestions for each ... Continue reading All suggestions for revision have been done well. Authors have added more interpretations of the results, linked them to previous studies and practice, and provided implications and suggestions for each section of the findings listed on Page 9 - Page 14.

Suggestions for further research, conducting a qualitative approach/empirical study, can also conduct Focus Group Discussions with the P2P Lending platform in Malaysia and capture the P2P Lending landscape. Propose ideas for the industry.

Good Luck!
All suggestions for revision have been done well. Authors have added more interpretations of the results, linked them to previous studies and practice, and provided implications and suggestions for each section of the findings listed on Page 9 - Page 14.

Suggestions for further research, conducting a qualitative approach/empirical study, can also conduct Focus Group Discussions with the P2P Lending platform in Malaysia and capture the P2P Lending landscape. Propose ideas for the industry.

Good Luck!
Competing Interests: No competing interests from us. Close
Report a concern
Respond or Comment

COMMENTS ON THIS REPORT

Author Response 04 Apr 2022

Thi Phuong Lan Nguyen, FACULTY OF MANAGEMENT, MULTIMEDIA UNIVERSITY, CYBERJAYA, 63100, Malaysia

04 Apr 2022

Author Response

Dear Prof. Dr. Ryan Randy Suryono,

First of all, we would like to express our sincere thanks and gratitude for being one of the reviewers for our research paper.
... Continue reading Dear Prof. Dr. Ryan Randy Suryono,

First of all, we would like to express our sincere thanks and gratitude for being one of the reviewers for our research paper.

Upon receiving all your constructed comments, we have revised and made corrections accordingly.

The following are our responses to your given comments:

1. For the comment #1: In the introduction, it is necessary to explain the reason for the research. Why was this research was conducted? Why Malaysia? This section has very few references.

We have added the justification for the study as suggested (see Page 3).

We have also added a section of literature review to show the related works and the gap in literature the study aims to fill in (see Page 3).

2. For the comment #2: The methodology section should be explained step by step. What is the process for determining the feasibility of a case study? What is the process of data collection and analysis until it becomes the research result?

We have added details of the sample of loan campaigns recorded from the nine P2P lending platforms (page 8).

The following table is added:

Table 1: Number of Loan Campaigns Recorded from January to May 2021 at the Nine Malaysian P2P Lending Platforms (Page 9)

We have also explained the analysis method used for the study (Page 8).

3. For the comment #3: The results section should produce an in-depth discussion. How are lessons learned from the findings? Do the results support other research? What are the theoretical and practical implications? Can the author also compare P2P Lending practices in other countries? It might be an interesting review if there are some benchmarks.

We have added more interpretation of the results, linked them to past studies and practices, and provided implications and suggestions to each finding section. (see Page 9 - Page 14)

4. For the comment #4: Overall, this article needs a lot of improvement in substance by enriching the study literature. Please correct the citation and proofread.

We have also added a section of literature review to show the related works and the gap in literature the study aims to fill in (see Page 3).

We have added more references and corrected citations as suggested.

The article has gone through a few rounds of proofreading. (see page 15 – 16)

We are looking forward to having further feedback and approval.

Many thanks,

On behalf of the team,

Lan Nguyen (Ph.D.)
Dear Prof. Dr. Ryan Randy Suryono,

First of all, we would like to express our sincere thanks and gratitude for being one of the reviewers for our research paper.

Upon receiving all your constructed comments, we have revised and made corrections accordingly.

The following are our responses to your given comments:

1. For the comment #1: In the introduction, it is necessary to explain the reason for the research. Why was this research was conducted? Why Malaysia? This section has very few references.

We have added the justification for the study as suggested (see Page 3).

We have also added a section of literature review to show the related works and the gap in literature the study aims to fill in (see Page 3).

2. For the comment #2: The methodology section should be explained step by step. What is the process for determining the feasibility of a case study? What is the process of data collection and analysis until it becomes the research result?

We have added details of the sample of loan campaigns recorded from the nine P2P lending platforms (page 8).

The following table is added:

Table 1: Number of Loan Campaigns Recorded from January to May 2021 at the Nine Malaysian P2P Lending Platforms (Page 9)

We have also explained the analysis method used for the study (Page 8).

3. For the comment #3: The results section should produce an in-depth discussion. How are lessons learned from the findings? Do the results support other research? What are the theoretical and practical implications? Can the author also compare P2P Lending practices in other countries? It might be an interesting review if there are some benchmarks.

We have added more interpretation of the results, linked them to past studies and practices, and provided implications and suggestions to each finding section. (see Page 9 - Page 14)

4. For the comment #4: Overall, this article needs a lot of improvement in substance by enriching the study literature. Please correct the citation and proofread.

We have also added a section of literature review to show the related works and the gap in literature the study aims to fill in (see Page 3).

We have added more references and corrected citations as suggested.

The article has gone through a few rounds of proofreading. (see page 15 – 16)

We are looking forward to having further feedback and approval.

Many thanks,

On behalf of the team,

Lan Nguyen (Ph.D.)
Competing Interests: No competing interests from us. Close
Report a concern
Reviewer Response 11 Apr 2022

Ryan Randy Suryono, Faculty of Engineering and Computer Science, Universitas Teknokrat Indonesia, Kota Bandar Lampung, Indonesia

11 Apr 2022

Reviewer Response

All suggestions for revision have been done well. Authors have added more interpretations of the results, linked them to previous studies and practice, and provided implications and suggestions for each ... Continue reading All suggestions for revision have been done well. Authors have added more interpretations of the results, linked them to previous studies and practice, and provided implications and suggestions for each section of the findings listed on Page 9 - Page 14.

Suggestions for further research, conducting a qualitative approach/empirical study, can also conduct Focus Group Discussions with the P2P Lending platform in Malaysia and capture the P2P Lending landscape. Propose ideas for the industry.

Good Luck!
All suggestions for revision have been done well. Authors have added more interpretations of the results, linked them to previous studies and practice, and provided implications and suggestions for each section of the findings listed on Page 9 - Page 14.

Suggestions for further research, conducting a qualitative approach/empirical study, can also conduct Focus Group Discussions with the P2P Lending platform in Malaysia and capture the P2P Lending landscape. Propose ideas for the industry.

Good Luck!
Competing Interests: No competing interests from us. Close
Report a concern

Views

Reviewer Report 10 Nov 2021

Dongwoo Kim, Research Institute, KB Financial Group Inc, Seoul, South Korea

Approved with Reservations

https://doi.org/10.5256/f1000research.77058.r98013

This study examined nine P2P lending platforms in Malaysia to determine the potential exposures faced by investors through various relationships between interest rates and risk classifying factors such as credit rating, industry, business stage, loan purpose and loan duration. This paper is meaningful in clarifying the relationship between interest rates and other information on multiple P2P lending platforms based in Malaysia for the first time. However, there are some issues that the author should address:

1. Citation: some of the references are not displayed in the body text.

2. Samples: it is necessary to clarify the number of samples for each platform to be analyzed.

3. Methods: it is necessary to clarify the reason for omitting the results of regression analysis and normality analysis as well as containing only the contents of descriptive statistics.

4. P2P lending is a field that has recently received a lot of attention academically and practically. Therefore, more and more related studies are being published. Among them, there are several studies that have revealed the relationship between various types of borrower information and loan interest rates, which are of interest to the authors, and should be investigated by them.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: P2P lending

CITE

Report a concern

Author Response 04 Apr 2022

Thi Phuong Lan Nguyen, FACULTY OF MANAGEMENT, MULTIMEDIA UNIVERSITY, CYBERJAYA, 63100, Malaysia

04 Apr 2022

Author Response

Dear Prof. Dr. Dongwoo Kim,

First of all, we would like to express our sincere thanks and gratitude for being one of the reviewers for our research paper.

... Continue reading Dear Prof. Dr. Dongwoo Kim,

First of all, we would like to express our sincere thanks and gratitude for being one of the reviewers for our research paper.

Upon receiving all your constructed comments, we have revised and made corrections accordingly.
The following are our responses to your given comments:

1. For the comment #1: Citation: some of the references are not displayed in the body text.

We have added more references and corrected citations as suggested.

2. For the comment #2: Samples: it is necessary to clarify the number of samples for each platform to be analyzed.

We have added details of the sample of loan campaigns recorded from the nine P2P lending platforms (page 8).

The following table is added:

Table 1: Number of Loan Campaigns Recorded from January to May 2021 at the Nine Malaysian P2P Lending Platforms (Page 9)

3. For the comment #3: Methods: it is necessary to clarify the reason for omitting the results of regression analysis and normality analysis as well as containing only the contents of descriptive statistics.

We have also explained the analysis method used for the study (Page 8).

4. For the comment #4: P2P lending is a field that has recently received a lot of attention academically and practically. Therefore, more and more related studies are being published. Among them, there are several studies that have revealed the relationship between various types of borrower information and loan interest rates, which are of interest to the authors, and should be investigated by them.

We have also added a section of literature review to show the related works and the gap in literature the study aims to fill in (see Page 3).

We are looking forward to having further feedback and approval.

Many thanks,

On behalf of the team,

Lan Nguyen (Ph.D.)
Dear Prof. Dr. Dongwoo Kim,

First of all, we would like to express our sincere thanks and gratitude for being one of the reviewers for our research paper.

Upon receiving all your constructed comments, we have revised and made corrections accordingly.
The following are our responses to your given comments:

1. For the comment #1: Citation: some of the references are not displayed in the body text.

We have added more references and corrected citations as suggested.

2. For the comment #2: Samples: it is necessary to clarify the number of samples for each platform to be analyzed.

We have added details of the sample of loan campaigns recorded from the nine P2P lending platforms (page 8).

The following table is added:

Table 1: Number of Loan Campaigns Recorded from January to May 2021 at the Nine Malaysian P2P Lending Platforms (Page 9)

3. For the comment #3: Methods: it is necessary to clarify the reason for omitting the results of regression analysis and normality analysis as well as containing only the contents of descriptive statistics.

We have also explained the analysis method used for the study (Page 8).

4. For the comment #4: P2P lending is a field that has recently received a lot of attention academically and practically. Therefore, more and more related studies are being published. Among them, there are several studies that have revealed the relationship between various types of borrower information and loan interest rates, which are of interest to the authors, and should be investigated by them.

We have also added a section of literature review to show the related works and the gap in literature the study aims to fill in (see Page 3).

We are looking forward to having further feedback and approval.

Many thanks,

On behalf of the team,

Lan Nguyen (Ph.D.)
Competing Interests: No competing interests from us Close
Report a concern
Respond or Comment

COMMENTS ON THIS REPORT

Author Response 04 Apr 2022

Thi Phuong Lan Nguyen, FACULTY OF MANAGEMENT, MULTIMEDIA UNIVERSITY, CYBERJAYA, 63100, Malaysia

04 Apr 2022

Author Response

Dear Prof. Dr. Dongwoo Kim,

First of all, we would like to express our sincere thanks and gratitude for being one of the reviewers for our research paper.

... Continue reading Dear Prof. Dr. Dongwoo Kim,

First of all, we would like to express our sincere thanks and gratitude for being one of the reviewers for our research paper.

Upon receiving all your constructed comments, we have revised and made corrections accordingly.
The following are our responses to your given comments:

1. For the comment #1: Citation: some of the references are not displayed in the body text.

We have added more references and corrected citations as suggested.

2. For the comment #2: Samples: it is necessary to clarify the number of samples for each platform to be analyzed.

We have added details of the sample of loan campaigns recorded from the nine P2P lending platforms (page 8).

The following table is added:

Table 1: Number of Loan Campaigns Recorded from January to May 2021 at the Nine Malaysian P2P Lending Platforms (Page 9)

3. For the comment #3: Methods: it is necessary to clarify the reason for omitting the results of regression analysis and normality analysis as well as containing only the contents of descriptive statistics.

We have also explained the analysis method used for the study (Page 8).

4. For the comment #4: P2P lending is a field that has recently received a lot of attention academically and practically. Therefore, more and more related studies are being published. Among them, there are several studies that have revealed the relationship between various types of borrower information and loan interest rates, which are of interest to the authors, and should be investigated by them.

We have also added a section of literature review to show the related works and the gap in literature the study aims to fill in (see Page 3).

We are looking forward to having further feedback and approval.

Many thanks,

On behalf of the team,

Lan Nguyen (Ph.D.)
Dear Prof. Dr. Dongwoo Kim,

First of all, we would like to express our sincere thanks and gratitude for being one of the reviewers for our research paper.

Upon receiving all your constructed comments, we have revised and made corrections accordingly.
The following are our responses to your given comments:

1. For the comment #1: Citation: some of the references are not displayed in the body text.

We have added more references and corrected citations as suggested.

2. For the comment #2: Samples: it is necessary to clarify the number of samples for each platform to be analyzed.

We have added details of the sample of loan campaigns recorded from the nine P2P lending platforms (page 8).

The following table is added:

Table 1: Number of Loan Campaigns Recorded from January to May 2021 at the Nine Malaysian P2P Lending Platforms (Page 9)

3. For the comment #3: Methods: it is necessary to clarify the reason for omitting the results of regression analysis and normality analysis as well as containing only the contents of descriptive statistics.

We have also explained the analysis method used for the study (Page 8).

4. For the comment #4: P2P lending is a field that has recently received a lot of attention academically and practically. Therefore, more and more related studies are being published. Among them, there are several studies that have revealed the relationship between various types of borrower information and loan interest rates, which are of interest to the authors, and should be investigated by them.

We have also added a section of literature review to show the related works and the gap in literature the study aims to fill in (see Page 3).

We are looking forward to having further feedback and approval.

Many thanks,

On behalf of the team,

Lan Nguyen (Ph.D.)
Competing Interests: No competing interests from us Close
Report a concern

Comments on this article Comments (0)

Version 3

VERSION 3 PUBLISHED 26 Oct 2021

Open Peer Review

Reviewer Status

Reviewer Reports

	Invited Reviewers
	1	2	3
Version 3 (revision) 14 Apr 23
Version 2 (revision) 04 Apr 22		read	read
Version 1 26 Oct 21	read	read

Dongwoo Kim, KB Financial Group Inc, Seoul, South Korea
Ryan Randy Suryono, Universitas Teknokrat Indonesia, Kota Bandar Lampung, Indonesia
Rachel J. Nam, Goethe University Frankfurt, Frankfurt, Germany

Loriana Pelizzon, Goethe University Frankfurt, Frankfurt, Germany

Comments on this article

All Comments(0)

Add a comment

Browse by related subjects

Back to all reports

Reviewer Report

16 Views

17 Oct 2022 | for Version 2

Rachel J. Nam, Leibniz Institute SAFE, Goethe University Frankfurt, Frankfurt, Germany

Loriana Pelizzon, Leibniz Institute SAFE, Goethe University Frankfurt, Frankfurt, Germany

16 Views Cite this report Responses(0)

Approved With Reservations

This study compares different SME P2P lending platforms in Malaysia and explores the relationship between credit risk (proxied by interest rates) and different loan characteristics of SME borrowers (loan purpose, duration, business cycle, and industry) using hand-collected data from 9 Malaysian P2P lending platforms regulated by the securities commission.

Given the low number of loans from these platforms (262 loans from 9 platforms), the authors claim the results from regression tests are inconclusive. Therefore, they provide instead simple descriptive evidence with correlational analyses. This study provides an original insight into Malaysia's current P2P lending platforms. The novelty of the study lies in their first attempt to use loan-level P2P data in Malaysia. One very interesting finding is the disconnect between credit risk (credit scores) and interest rates persistent across many platforms. They find that the credit ratings given by the nine Malaysian P2P lending platforms cannot be used as predictors for SMEs’ default risks. This finding is particularly salient for investor protection purposes since misrepresentation of credit risk can be costly for investors but also for the platform.

Additionally, they also find that loans with similar loan purposes and durations may also provide investors with different interest rates. Based on these findings, they claim that these factors are not important in explaining potential risks associated with the loans. However, I have reservations with respect to drawing causal inferences using simple univariate comparisons. Without controlling for other factors that may be driving the outcome variable (interest rate), the authors should be cautious of making causal claims.

These points are further elaborated on below:

Could add further explanations in the literature section as to why credit ratings given by P2P platforms are often not reliable? This is contrary to many studies showing the effectiveness of credit scores given by online lenders who leverage alternative data (i.e. Li, Chen & Zeng, 2018; Mi, Hu & Deer, 2018).¹^,² But many studies argue that platform scores using alternative data sources can robustly predict default rates and sometimes outperform traditional credit, For instance, soft information in marketplace lending (Iyer et al. 2016),³ friendship, social network, group leader data (Hildebrand et al. 2017; Lin et al. 2013)⁴^,⁵, as well as text-based analysis of applicants listings (Gao et al. 2021; Dorfleitner et al. 2016; Netzer et al. 2019).⁶^,{ref-7]^,⁸ These studies show non-traditional data used by FinTech lenders improve the predictive power of risk assessment.
“For individual borrowers, characteristics such as age, education level, income level, gender, residential location, employment status, etc., may hinder the borrower’s attitude and behaviour towards loan repayment.”
- This sentence isn’t so clear. First, what does it mean to “hinder the borrower’s attitude towards loan repayment”? Do you simply mean, these factors are incomplete measures of default probability?
Figure 1. Credit rating and interest rate: These graphs are too crowded and hard to interpret at first.
Yet, a very intriguing finding that credit ratings on P2P platforms do not always reflect default probability. Could the authors provide further explanations as to why this may be happening? If credit rating is one of the most important criteria for most lending institutions, why is there such a big disconnect between credit rating and interest rate? Do we know if these credit scores are credit bureau-provided scores or platform-provided scores (credit bureau + alternative data)? The discrepancy is understandable for the former case, but for the latter, a further explanation is needed (i.e. measurement error? Manipulation by the platform? Etc).
The authors state that “The default misrepresenting credit ratings may be due to incomplete information given by the Malaysian SMEs to their respective nine P2P lending platforms, which may lead to a poor prediction on their defaults later”
- Can the authors test this theory by looking at the correlation between the interest rate/credit score and how much information was provided by the borrowers on each platform?
- This still does not explain why there is a misrepresentation of credit ratings. For instance, a firm provides very little information, and gets subsequently charged a higher interest rate. Wouldn’t this also be reflected in the credit score?
Figure 2. Interest rate and loan purpose: The authors state that “…. different interest rates are applied to SMEs whose loan purposes are the same at the nine individual P2P lending platforms. This may suggest that the nine P2P lending forms do not differentiate risk levels among different financial activities associated with their loans." This is a univariate comparison. Without accounting for other factors that are correlated with loan purpose which may also affect the outcome variable (interest rate), one should be careful in drawing a causal inference. For instance, the level of risk associated with business expansion for a young SME vs. a more established and older SME could be drastically different, which will translate into two different interest rates. This does not imply that P2P platforms do not differentiate risk levels among different loan purposes.
Figure 3. Interest rates and loan durations: The same concerns apply. Differences in interest rates applied to loans with similar maturities may be driven by other factors. Without controlling for all factors that matter for one’s credit risk, the authors should not draw a causal inference. For instance, the authors claim based on a univariate comparison that “the insignificant relationship between loan terms and interest rates suggests that a loan with a longer duration is not necessarily viewed as having a higher probability of default at the nine Malaysian P2P lending platforms. Therefore, it should not be charged with a higher interest rate than one with a shorter duration.” This statement is simply not true if the loan with a shorter maturity is given to a firm that is inherently riskier in other aspects compared to the firm that is getting a loan with a longer maturity. The positive relationship between loan maturity and risk may still be there if all the other risk factors are controlled for.
Figure 5: the same comments apply.
Study limitation: all the analyses are driven by univariate comparisons. This is a correlation study, thus causal interpretations should be interpreted with caution.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Partly

References

1. Li Q, Chen L, Zeng Y: The mechanism and effectiveness of credit scoring of P2P lending platform. China Finance Review International. 2018; 8 (3): 256-274 Publisher Full Text
2. Mi J, Hu T, Deer L: User Data Can Tell Defaulters in P2P Lending. Annals of Data Science. 2018; 5 (1): 59-67 Publisher Full Text
3. Iyer R, Khwaja A, Luttmer E, Shue K: Screening Peers Softly: Inferring the Quality of Small Borrowers. Management Science. 2016; 62 (6): 1554-1577 Publisher Full Text
4. Hildebrand T, Puri M, Rocholl J: Adverse Incentives in Crowdfunding. Management Science. 2017; 63 (3): 587-608 Publisher Full Text
5. Lin M, Prabhala N, Viswanathan S: Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending. Management Science. 2013; 59 (1): 17-35 Publisher Full Text
6. Dorfleitner G, Priberny C, Schuster S, Stoiber J, et al.: Description-text related soft information in peer-to-peer lending – Evidence from two leading European platforms. Journal of Banking & Finance. 2016; 64: 169-187 Publisher Full Text
7. Netzer O, Lemaire A, Herzenstein M: When Words Sweat: Identifying Signals for Loan Default in the Text of Loan Applications. Journal of Marketing Research. 2019; 56 (6): 960-980 Publisher Full Text
8. Gao Q, Lin M: Linguistic Features and Peer-to-Peer Loan Quality: A Machine Learning Approach. SSRN Electronic Journal. 2013. Publisher Full Text

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

FinTech, crypto and blockchains

We confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however we have significant reservations, as outlined above.

Respond to this report

Responses (0)

Back to all reports

Reviewer Report

14 Views

11 Apr 2022 | for Version 2

Ryan Randy Suryono, Faculty of Engineering and Computer Science, Universitas Teknokrat Indonesia, Kota Bandar Lampung, Indonesia

14 Views Cite this report Responses(0)

Approved

I have no further comment.

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Fintech; Financial Technology; P2P Lending; Peer to Peer Lending; Information System

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Respond to this report

Responses (0)

Back to all reports

Reviewer Report

17 Views

04 Mar 2022 | for Version 1

Ryan Randy Suryono, Faculty of Engineering and Computer Science, Universitas Teknokrat Indonesia, Kota Bandar Lampung, Indonesia

17 Views Cite this report Responses(2)

Approved With Reservations

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

References

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Fintech; P2P Lending

Respond to this report

Responses (2)

Author Response

04 Apr 2022

Thi Phuong Lan Nguyen, FACULTY OF MANAGEMENT, MULTIMEDIA UNIVERSITY, CYBERJAYA, 63100, Malaysia

Dear Prof. Dr. Ryan Randy Suryono,

First of all, we would like to express our sincere thanks and gratitude for being one of the reviewers for our research paper.

Upon receiving all your constructed comments, we have revised and made corrections accordingly.

The following are our responses to your given comments:

1. For the comment #1: In the introduction, it is necessary to explain the reason for the research. Why was this research was conducted? Why Malaysia? This section has very few references.

We have added the justification for the study as suggested (see Page 3).

We have also added a section of literature review to show the related works and the gap in literature the study aims to fill in (see Page 3).

2. For the comment #2: The methodology section should be explained step by step. What is the process for determining the feasibility of a case study? What is the process of data collection and analysis until it becomes the research result?

We have added details of the sample of loan campaigns recorded from the nine P2P lending platforms (page 8).

The following table is added:

Table 1: Number of Loan Campaigns Recorded from January to May 2021 at the Nine Malaysian P2P Lending Platforms (Page 9)

We have also explained the analysis method used for the study (Page 8).

3. For the comment #3: The results section should produce an in-depth discussion. How are lessons learned from the findings? Do the results support other research? What are the theoretical and practical implications? Can the author also compare P2P Lending practices in other countries? It might be an interesting review if there are some benchmarks.

We have added more interpretation of the results, linked them to past studies and practices, and provided implications and suggestions to each finding section. (see Page 9 - Page 14)

4. For the comment #4: Overall, this article needs a lot of improvement in substance by enriching the study literature. Please correct the citation and proofread.

We have also added a section of literature review to show the related works and the gap in literature the study aims to fill in (see Page 3).

We have added more references and corrected citations as suggested.

The article has gone through a few rounds of proofreading. (see page 15 – 16)

We are looking forward to having further feedback and approval.

Many thanks,

On behalf of the team,

Lan Nguyen (Ph.D.)

View more View less

Competing Interests

No competing interests from us.

Reviewer Response

11 Apr 2022

Ryan Randy Suryono, Faculty of Engineering and Computer Science, Universitas Teknokrat Indonesia, Kota Bandar Lampung, Indonesia

All suggestions for revision have been done well. Authors have added more interpretations of the results, linked them to previous studies and practice, and provided implications and suggestions for each section of the findings listed on Page 9 - Page 14.

Suggestions for further research, conducting a qualitative approach/empirical study, can also conduct Focus Group Discussions with the P2P Lending platform in Malaysia and capture the P2P Lending landscape. Propose ideas for the industry.

Good Luck!

View more View less

Competing Interests

No competing interests from us.

Back to all reports

Reviewer Report

22 Views

10 Nov 2021 | for Version 1

Dongwoo Kim, Research Institute, KB Financial Group Inc, Seoul, South Korea

22 Views Cite this report Responses(1)

Approved With Reservations

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

P2P lending

Respond to this report

Responses (1)

Author Response

04 Apr 2022

Thi Phuong Lan Nguyen, FACULTY OF MANAGEMENT, MULTIMEDIA UNIVERSITY, CYBERJAYA, 63100, Malaysia

Dear Prof. Dr. Dongwoo Kim,

First of all, we would like to express our sincere thanks and gratitude for being one of the reviewers for our research paper.

Upon receiving all your constructed comments, we have revised and made corrections accordingly.
The following are our responses to your given comments:

1. For the comment #1: Citation: some of the references are not displayed in the body text.

We have added more references and corrected citations as suggested.

2. For the comment #2: Samples: it is necessary to clarify the number of samples for each platform to be analyzed.

We have added details of the sample of loan campaigns recorded from the nine P2P lending platforms (page 8).

The following table is added:

Table 1: Number of Loan Campaigns Recorded from January to May 2021 at the Nine Malaysian P2P Lending Platforms (Page 9)

3. For the comment #3: Methods: it is necessary to clarify the reason for omitting the results of regression analysis and normality analysis as well as containing only the contents of descriptive statistics.

We have also explained the analysis method used for the study (Page 8).

4. For the comment #4: P2P lending is a field that has recently received a lot of attention academically and practically. Therefore, more and more related studies are being published. Among them, there are several studies that have revealed the relationship between various types of borrower information and loan interest rates, which are of interest to the authors, and should be investigated by them.

We have also added a section of literature review to show the related works and the gap in literature the study aims to fill in (see Page 3).

We are looking forward to having further feedback and approval.

Many thanks,

On behalf of the team,

Lan Nguyen (Ph.D.)

View more View less

Competing Interests

No competing interests from us

Alongside their report, reviewers assign a status to the article:

Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions

[1] Bloomberg News: How China’s Peer-to-Peer Lending Crash Is Destroying Lives.2018.Reference Source

[2] Business Wire: Global Peer to Peer (P2P) Lending Market Trends, Growth, Opportunity Report 2020-2025 - ResearchAndMarkets.com.2020 December 15, 2020.

[3] Chen X, Chong Z, Giudici P, et al.: Networking with Peers: Evidence from a P2P Lending Platform. Asian Development Bank Institute, Working Paper No.1080, February 2020.2020.

[4] Gibilara L, Mattarocci G: Peer-to-Peer lending and real estate mortgages: Evidence from the United Kingdom. J. Euro. Real Estate Res. 2018; 11(3): 319–334. Publisher Full Text

[5] Gonsalez L: Blockchain, herding and trust in peer-to-peer lending. Manag. Finance 2019; 46: 815–831. Publisher Full Text

[6] He Q, Li X: The Failure of Chinese Peer-to-Peer Lending Platforms: Finance and Politics. J. Corp. Finan. 2021; 66: 101852. Publisher Full Text

[7] Hidajat T: Unethical practices peer-to-peer lending in Indonesia. J. Finan. Crime. 2020; 27(1): 274–282. Publisher Full Text

[8] Kim D: Bounded rationality in a P2P lending market. Review of Behavioral Finance. 2020; 13: 184–201. Publisher Full Text

[9] Kok C: Asset Quality of P2P Players Remain inact. Star. 2021.May 22 2021.Reference Source

[10] Li Q: the Mechanism and Effectiveness of Credit Scoring of P2P Lending Platform: Evidence from Renrendai.com. China Finance Review International. 2018; 8(3): 256–274. Publisher Full Text

[11] Lusardi A, Mitchell OS: Planning and Financial Literacy: How Do Women Fare?. Am. Econ. Rev. 2008; 98: 413–417. Publisher Full Text

[12] Nemoto N, Storey D, Huang B: Optimal Regulation of P2P Lending for Small and Medium-Sized Enterprises. Asian Development Bank Institute, Working Paper No. 912.2019.

[13] Nguyen TPL: Data Source_P2P Lending Platforms in Malaysia: What Do We Know? figshare. Dataset. 2021. Publisher Full Text

[14] Rosavina M, Rahadi RA, Kitri ML, et al.: P2P lending adoption by SMEs in Indonesia. Qualitative Research in Financial Markets. 2019; 11(2): 260–279. Publisher Full Text

[15] San-Jose L, Retolaza JL: Crowdlending as a socially innovative corporate financial instrument. Int. Perspectives on Crowdfunding. 2017; 129–149.

[16] Shi X, Wu J, Hollingsworth J: How does P2P lending platform reputation affect lenders ‘decision in China?. Int. J. Bank Mark. 2019; 37(7): 1566–1589. Publisher Full Text

[17] Stern C, Makinen M, Qian Z: FinTechs in China – with a special focus on peer-to-peer lending. J. Chinese Economic and Foreign Trade Studies. 2017; 10(3): 215–228. Publisher Full Text

[18] Trönnberg CC, Hemlin S: Lending decision making in banks: A critical incident study of loan officers. Eur. Manag. J. 2014; 32(2): 362–372. Publisher Full Text

[19] The World Bank Group: The little data book on Financial Inclusion. The Global Findex database.2017.Reference Source

[20] Zhe KSK: P2P Financing Industry Growing. the Edge Malaysia. 2019.December 26, 2019.Reference Source

P2P lending platforms in Malaysia: What do we know?

Abstract

Keywords

Introduction

Methods

Statistical analysis

Results/discussion

Subscription requirements at P2P lending platforms

Table 1. Required documents for investors at nine P2P lending platforms in Malaysia.

Credit rating and interest rate

Figure 1. Interest rates and credit ratings at nine P2P lending platforms.

Interest rate and loan purpose

Figure 2. Interest rates and loan purposes at nine P2P lending platforms.

Interest rate and loan duration

Figure 3. Interest rates and loan durations at nine P2P lending platforms.

Interest rates and business cycles

Figure 4. Interest rates and stages of business at nine P2P lending platforms.

Interest rate and industry

Figure 5. Interest rates and industries at nine P2P lending platforms.

Study limitation

Conclusion

Data availability

Underlying data

Ethical approval

Author contributions

Acknowledgement

References

Comments on this article Comments (0)

Open Peer Review

Comments on this article Comments (0)

Open Peer Review

Reviewer Status

Reviewer Reports

Comments on this article

Browse by related subjects

Competing Interests Policy

Stay Updated