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This study aims to develop a theoretical model that uses the decision-making theory in a financial intermediation setting to provide insights into the differences between the outcomes of the decision-making process for a bank and for a peer-to-peer (p2p) lending platform to explain the role of p2p lending versus bank lending in the credit market.

This study develops a novel approach to explaining the differences between p2p lending and bank lending by using the decision-making theory. In particular, it analyzes the likelihood of a risky borrower being able to obtain a loan from a p2p lending platform versus the likelihood of being able to obtain a loan from a bank. The results contribute a theoretical understanding of factors that can determine the role of p2p lending platforms versus that of banks in the credit market, with implications for recovery from an economic crisis.

p2p lending platforms have the potential for contributing to economic recovery when they are subject to less regulations and are able to offer a faster and less costly lending process than do banks and when they are used by a large number of lenders. However, the potential role of p2p lending platforms in recovery might be reduced when banks have access to anticyclical measures that reduce banks’ capital requirements or provide them with low-cost funds.

This study provides a novel approach to explaining the differences between p2p lending and bank lending by using the decision-making theory. The results contribute a theoretical understanding of factors that can determine the role of p2p lending platforms versus that of banks in the credit market.

Despite a large stake of investment by retail investors and a growing number of peer-to-peer (P2P) lending platforms coupled with the initiation of secondary market and strong regulatory framework, less is known what leads investors to trust in P2P (TP2P) lending platforms in a multi-ethnic country, Malaysia. This study aims to investigate the effects of individual characteristics (gender, age, ethnicity, education and income), social influence of P2P (SIP2P) lending and privacy of P2P (PP2P) lending on the trust in emerging P2P platforms.

A cross-sectional survey was conducted to collect the data from retail investors in Malaysia. A variance-based partial least squares-structural equation modeling (PLS-SEM) model was applied to examine the significant predictors of TP2P lending platforms.

The results show that while investors' income is positively related to TP2P lending platforms, younger investors are less likely to have trust on P2P lending platforms. PP2P lending platforms increases retail investors' trust toward P2P platforms in Malaysia.

P2P service providers are suggested to give especial attention to investors' specific characteristics to develop trust and attract investors to the platforms. Service providers need to ensure the privacy of potential investors' personal and confidential data to build investors' trust.

This is the first study to assess retail investors' trust toward online P2P lending platforms in Malaysia, where this alternative financing platform gradually gaining popularity.

This study aims to analyze the relationship between financial sustainability and peer-to-peer (P2P) lending platforms.

To do so, an extensive literature review on sustainability, FinTech, P2P lending and their associated risks was conducted using a fundamentally theoretical and descriptive methodology.

In addition, this study shows that finance can accelerate the transition to a low-carbon circular economy by allocating investments in sustainable projects and businesses. Moreover, FinTech P2P lending platforms can help to vitalize green digital finance by using the internet and information technology in the lending market. Nevertheless, anonymous lending and borrowing ventures can produce potential risks such as money laundering, terrorist financing, fraud risk and information asymmetry.

Sustainable finance remains an emerging and relevant area; however, the literature has not sufficiently addressed compliance concerns. To address this gap, this study aims to contribute to the literature by analyzing the link between sustainable finance and P2P platforms and drawing attention to the compliance risks listed above.

The research documented in this paper aims to examine multiple factors related to borrowers' default in peer-to-peer (P2P) lending in the USA. This study is motivated by the hypothesis that both P2P loan characteristics and macroeconomic variables have influence on loan performance. The authors define a set of loan characteristics, borrower characteristics and macroeconomic variables that are significant in determining the probability of default and should be taken into consideration when assessing credit risk.

The research question in this study is to find the significant explanatory variables that are essential in determining the probability of default for LendingClub loans. The empirical study is based on a total number of 1,863,491 loan records issued through LendingClub from 2007 to 2020Q3 and a logistic regression model is developed to predict loan defaults.

The results, in line with prior research, show that a number of borrower and contractual loan characteristics predict loan defaults. The innovation of this study is the introduction of specific macroeconomic indicators. The study indicates that macroeconomic variables assessed alongside loan data can significantly improve the forecasting performance of default model. The general finding demonstrates that higher percentage change in House Price Index, Consumer Sentiment Index and S&P500 Index is associated with a lower probability of delinquency. The empirical results also exhibit significant positive effect of unemployment rate and GDP growth rate on P2P loan default rates.

The results have important implications for investors for whom it is of great importance to know the determinants of borrowers' creditworthiness and loan performance when estimating the investment in a certain P2P loan. In addition, the forecasting performance of the model could be applied by authorities in order to deal with the credit risk in P2P lending and to prevent the effects of increasing defaults on the economy.

This paper fulfills an identified need to shed light on the association between specific macroeconomic indicators and the default risk from P2P lending within an economy, while the majority of the existing literature investigate loan and borrower information to evaluate credit risk of P2P loans and predict the likelihood of default.

This study aims to provide a better comprehension of the behavioural intentions that influence the adoption of Islamic financial technology (Fintech) in Malaysia for two kinds of Islamic lending Fintech services, which are crowdfunding and peer-to-peer (P2P) lending.

From May to July 2022 the primary data were collected by using a questionnaire distributed online to survey 437 Islamic Fintech clients in Malaysia. Structural equation modelling has been used to analyse the data based on using the partial least squares approach.

The findings of this paper shows that planned behaviour, acceptance model and technology's use models are positively impacting factors that influence customers' opinions on adapting Islamic Fintech services in lending. The acceptance model was found to exert a negative impact on the intention to adopt Islamic lending P2P Fintech service. In addition, technology's use has a negative impact on the intention to adopt Islamic lending crowdfunding Fintech service.

First, the study is limited to Islamic Fintech customers in Malaysia only, second, the study adopted an online survey but there is no guarantee that the geography area was fully covered. Another limitation is that the study covers only Islamic Fintech services in lending, thus the study did not attend to variables such as religiosity and the authors believe that this will provide useful insights for future research.

Despite the importance of this topic, there has been a lack of empirical evidence until now. In this paper, the authors take stock of the empirical evidence in the literature through the importance of the adoption Fintech. This study provides a broad view of the market potentials for Fintech providers from the demand side on a wide range of Islamic Fintech services rather than focussing only on payment, transfer, etc. as presented in previous studies.

This paper aims at shedding light on the entrepreneurs' perception towards crowdfunding as a new mean for raising capital, and their willingness to send appropriate signals to the potential fund providers/backers.

The research strategy is based on three methodological approaches: desk research on online sources, a map of the crowdfunding phenomenon, and a quantitative approach with a survey performed between June and December 2020. The survey covers a sample of 147 Small and Medium enterprises (SMEs) and startups, in addition to semi-structured interviews with 10 entrepreneurs.

The study reveals that between losing their work and losing part of their firms' equity, entrepreneurs are keen on sending positive signals to backers. Moreover, they are willing to adopt a new way of thinking, as their primary goal is to save their firms, their jobs, and their source of income. The research highlights the concern of entrepreneurs of losing reputation, losing intellectual property, losing control, and of becoming only shareholders in their enterprises.

The main limitation in this paper is that no single study in Lebanon adequately covers the topic and thus extensive research has been carried out on crowdfunding across the world and analyzed in the Lebanese context.

Overcoming funding challenges can reduce brain drain, promote a culture of entrepreneurship, serve the economy, combat poverty, achieve more equitable society, increase the levels of expectations, and turn the flywheel. Moreover, the paper presents clear implications for the field of policy-making both in developing and developed countries.

Considering the serious financial disintermediation and liquidity shortage Lebanon faces, the findings of this study show how important changing entrepreneurial culture and behavior is, and the crucial role crowdfunding could play in providing funds for the SMEs that form 95% of the total business sector in Lebanon.

Social interaction in comment sections has become a key factor for backers' decision making in crowdfunding platforms. However, current research on the two-way social interaction in crowdfunding is insufficient, and there exist inconsistent conclusions. This study focuses on the social interaction between creators and backers and explores its influence on the successful exit of crowdfunding projects.

The extended Cox model is used for the empirical analysis of 1,988 crowdfunding projects on the Modian (www.modian.com) platform, a crowdfunding platform for cultural and creative projects in China. The two-way social interaction is reflected in comment quantity and sentiment, as well as reply rate.

Results reveal an inverted U-shaped relationship between comment quantity/sentiment and the successful exit of crowdfunding projects. This relationship is strengthened by high reply rate.

This study focuses on comment quantity and sentiment. The inverted U-shaped results reconcile previous conclusions. Replies from creators are regarded as a separate factor, and their moderating role is explained. The study research proves the importance of social interaction in crowdfunding platforms and provides suggestions for backers, creators and platform managers.

With the rapid growth of the domestic lending industry, assessing whether the borrower of each loan is at risk of default is a pressing issue for financial institutions. Although there are some models that can handle such problems well, there are still some shortcomings in some aspects. The purpose of this paper is to improve the accuracy of credit assessment models.

In this paper, three different stages are used to improve the classification performance of LSTM, so that financial institutions can more accurately identify borrowers at risk of default. The first approach is to use the K-Means-SMOTE algorithm to eliminate the imbalance within the class. In the second step, ResNet is used for feature extraction, and then two-layer LSTM is used for learning to strengthen the ability of neural networks to mine and utilize deep information. Finally, the model performance is improved by using the IDWPSO algorithm for optimization when debugging the neural network.

On two unbalanced datasets (category ratios of 700:1 and 3:1 respectively), the multi-stage improved model was compared with ten other models using accuracy, precision, specificity, recall, G-measure, F-measure and the nonparametric Wilcoxon test. It was demonstrated that the multi-stage improved model showed a more significant advantage in evaluating the imbalanced credit dataset.

In this paper, the parameters of the ResNet-LSTM hybrid neural network, which can fully mine and utilize the deep information, are tuned by an innovative intelligent optimization algorithm to strengthen the classification performance of the model.

The rapid growth of Fintech presents a growing challenge for banking institutions, particularly those with more traditional, service backgrounds. This paper aims to examine the relationship between Fintech innovation and bank performance by exploiting novel Chinese market data.

Guided by the work of Dietrich and Wanzenried (2011, 2014) and Phan et al. (2019), the authors construct a regression model to investigate the effect of Fintech innovation on the profitability of Chinese listed banks. The authors include their measures of Fintech innovation in each of their selected structures.

Results indicate that Fintech innovation is negatively associated with bank performance and that state-owned banks, joint-stock commercial banks and long-established banks are more negatively impacted by Fintech innovation relative to city and rural commercial banks and younger banks.

Risk tolerance levels, internal structure and efficiency and recent debt repayment performance channels are each shown to be significant, robust explanatory factors underpinning such results.

The purpose of this study is to identify motivations for the uptake of crowdfunding by micro-entrepreneurs in an emerging economy and the extent to which these vary by entrepreneur characteristics, sector and crowdfunding model.

The authors conduct qualitative analyses of data collected in interviews with 57 micro-entrepreneurs in Morocco, all of whom used crowdfunding in fundraising.

The authors identify six key motives for crowdfunding adoption by micro-entrepreneurs including financing needs, legitimacy seeking, sense of achievement, network-building, entrepreneurial and marketing competence enhancements. They also find evidence for moderation effects of fundraiser characteristics on likelihood of adoption, including gender, age, education, training experience and sectoral affiliation. Furthermore, the authors show that the relative importance of different motives varies by the type of crowdfunding model used.

The original aspects of the study include the examination of adoption motives in an emerging market context and the distinguishing between entrepreneurs’ adoption motives based on different gender, age, education, training experience, sectoral affiliation and crowdfunding model used. Moreover, the authors show that enhancement of competencies is a more dominant motive in the emerging market context than mentioned in earlier studies in developed contexts.