Does Borrower Domicile Influence the Credit Default in P2P Lending? Preliminary Analysis from Indonesia

Purpose: Credit risk is one of the most fundamental risks that P2P lending platforms have. The magnitude of information asymmetry, consumer behavior, and the unequal distribution of financial literacy make credit risk in P2P lending more vulnerable in several parts of Indonesia. The purpose of this study was to determine the domicile of the borrower on the credit risk in P2P lending Methodology: We use time series data from January 2018-December 2021 for analysis. Vector Error Correction Model (VECM) is used to analyze the data. Findings: The results show that borrowers domiciled outside Java influence the credit default significantly positively, while borrowers domiciled in Java influence credit default significantly negatively. Moreover, interest rate influences positively significant on P2P lending default, while inflation influences positively on P2P lending default. Novelty: this paper is the first paper to analyze the P2P credit default in Indonesia using time series analysis.

Determinants of default in the bitcoin lending market. The case of Bitbond platform

This paper studies the bitcoin lending market and the factors explaining loans defaults. No financial intermediation implies that investors are faced directly with the credit risk. This increases information asymmetry at the cost of the lenders, so bitcoin lending platforms try to reduce this negative effect by providing information about the borrowers and their loan requests. Credit grade and interest rate are assigned by the platform, which are the main variables of the interest. This study has been conducted on the largest active bitcoin lending platform Bitbond covering 2013-2017 period with overall (N=1449) loans outstanding. Correlation analysis and univariate means tests have been used to analyse the data, while logistic regressions have been used for predicting default. Factors explaining default are loan amount, loan term and purpose of working capital, as well as industry of education and transportation and the total number of identifications. The interest rate assigned is the most predictive factor of the default followed by the grade, though other additional variables still improve the accuracy of the models. This paper contributes to the current literature since it is the first, to the best of our knowledge, analysing the bitcoin lending market

The value of personal credit history in risk screening of entrepreneurs:Evidence from marketplace lending

We explore the quality of risk assessment for entrepreneurs/small business borrowers as compared to consumers, when the same information on previous credit history is used for both segments in marketplace lending. By building several cross-sectional logistic regression and machine-learning models and applying them separately to small business loans (SBL) and consumers we can measure models’ predictive accuracy for different segments, and thus, make observations about the value of the information used for screening. We find the differences in profiles between SBL and consumers, hence they should be assessed by separate models. Yet separate SBL models do not perform well when applied to a future time period. We attribute this to the relatively low predictive value of personal credit history for entrepreneurs as compared to the consumers. We advocate the use of additional information for risk assessment of entrepreneurs, in order to improve the quality of credit screening. This should lead to improved access of small business borrowers to credit in situations when they have to compete with consumers for funding

Is information transparency important for funders? A case study of sharia P2P lending companies in Indonesia

Research aims: This study explores the importance of information transparency for funders as parties who provide funding to borrowers' projects. It also analyzes information transparency practices in sharia P2P lending. Design/Methodology/Approach: The study used a qualitative case study, focusing on three sharia P2P lending companies in Indonesia. Data were collected through interviews with parties from three sharia P2P lending companies and 11 funders. Research findings: It was found that information transparency is important for funders, increasing their confidence to invest. In addition, based on multiple agency theory, there is information asymmetry between funders and sharia P2P lending borrowers, which can be reduced by information transparency measures from funders, sharia P2P lending, and borrowers based on cost-benefit considerations. Theoretical contribution/Originality: This research explores the application of information transparency in sharia P2P lending companies, which, as far as researchers are concerned, has not been raised in previous studies. In addition, the study builds a conceptual framework of information transparency in sharia P2P lending companies based on multiple agency theory. Practitioner implication: The research has implications for applying information transparency in sharia P2P lending, which can improve information updates and communication from sharia P2P lending to its funders. Research limitation/Implication: The study only focused on three out of the seven sharia P2P lending in Indonesia. Therefore, the differences in business, focus, and other characteristics of the remaining four were not considered

Disrupting Finance

This open access Pivot demonstrates how a variety of technologies act as innovation catalysts within the banking and financial services sector. Traditional banks and financial services are under increasing competition from global IT companies such as Google, Apple, Amazon and PayPal whilst facing pressure from investors to reduce costs, increase agility and improve customer retention. Technologies such as blockchain, cloud computing, mobile technologies, big data analytics and social media therefore have perhaps more potential in this industry and area of business than any other. This book defines a fintech ecosystem for the 21st century, providing a state-of-the art review of current literature, suggesting avenues for new research and offering perspectives from business, technology and industry

Essays on the Economics of Peer-to-Peer Lending

This thesis presents three empirical studies about the peer-to-peer (P2P) lending market. The first study examines whether the announcement of a government support policy could have an impact on the P2P lending market, using the U.K.’s introduction of a tax-free P2P individual savings account as an example. I find that after the announcement of the new policy, high-risk borrowers were attracted into the market and this resulted in losses to lenders. The second study is a discussion of how a Ponzi scheme affected Chinese P2P lending platforms. I find that after the Ezubao Ponzi scheme, platforms suffered a higher default risk and paid higher premiums to cover lenders’ losses, which resulted in negative returns for P2P lending platforms. The third study examines the lifecycle of the development of the P2P lending market in China. Based on the industry lifecycle (ILC) theory, I find that the P2P lending market in China experienced rapid growth and then a significant decline in 13 years. Even though the lifespan of the market is short, the market can still be pictured as having five phases of development. In line with theoretical predictions, the earliest entrants among P2P lending platforms survived the longest in the market