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Lenders in online peer-to-peer (P2P) lending platforms are always non-experts and face severe information asymmetry. This paper aims to achieve the goals of gaining high returns with risk limitations or lowering risks with expected returns for P2P lenders.

This paper used data from a leading online P2P lending platform in America. First, the authors constructed a logistic regression-based credit scoring model and a linear regression-based profit scoring model to predict the default probabilities and profitability of loans. Second, based on the predictions of loan risk and loan return, the authors constructed linear programming model to form the optimal loan portfolio for lenders.

The research results show that compared to a logistic regression-based credit scoring method, the proposed new framework could make more returns for lenders with risks unchanged. Furthermore, compared to a linear regression-based profit scoring method, the proposed new framework could lower risks for lenders without lowering returns. In addition, comparisons with advanced machine learning techniques further validate its superiority.

Unlike previous studies that focus solely on predicting the default probability or profitability of loans, this study considers loan allocation in online P2P lending as an optimization research problem using a new framework based upon modern portfolio theory (MPT). This study may contribute theoretically to the extension of MPT in the specific context of online P2P lending and benefit lenders and platforms to develop more efficient investment tools.

This study aims to assess the default risk of borrowers in peer-to-peer (P2P) online lending platforms. The authors propose a novel default risk classification model based on data cleaning and feature extraction, which increases risk assessment accuracy.

The authors use borrower data from the Lending Club and propose the risk assessment model based on low-rank representation (LRR) and discriminant analysis. Firstly, the authors use three LRR models to clean the high-dimensional borrower data by removing outliers and noise, and then the authors adopt a discriminant analysis algorithm to reduce the dimension of the cleaned data. In the dimension-reduced feature space, machine learning classifiers including the k-nearest neighbour, support vector machine and artificial neural network are used to assess and classify default risks.

The results reveal significant noise and redundancy in the borrower data. LRR models can effectively clean such data, particularly the two LRR models with local manifold regularisation. In addition, the supervised discriminant analysis model, termed the local Fisher discriminant analysis model, can extract low-dimensional and discriminative features, which further increases the accuracy of the final risk assessment models.

The originality of this study is that it proposes a novel default risk assessment model, based on data cleaning and feature extraction, for P2P online lending platforms. The proposed approach is innovative and efficient in the P2P online lending field.

The paper focuses on the variables that help analyze peer-to-peer (P2P) lending platforms. It explores the characteristic factors of identifying problematic platforms, and designs a P2P platform risk early warning model.

With the help of web crawler software, this paper crawls the information of 1427 P2P platforms from the two largest third-party lending information platforms (i.e. P2Peye and WDZJ) in China. SPSS 22.0 was mainly used for basic descriptive statistical analysis, reliability and validity analysis, and regression analysis of the data. MPLUS 7.0 was used for confirmatory factor analysis and structural equation models analysis.

Based on the multi-dimensional information, this paper performs text mining to develop an investor sentiment index. This study shows that the characteristics of the platform (i.e. basic features, capital security, operations management, and social network) have a significant impact on identifying problematic platforms.

There are some limitations to this research. In the process of model construction, some external factors may be ignored, such as government policies. Future research will need to consider the impact of policy and other factors more comprehensively on P2P lending platform risk identification.

This study proposes an effective method for investors and regulators to identify the risk factors of P2P lending platforms. The research findings provide valuable insights for promoting government participation in platform management as well as a healthy development of the P2P lending industry.

The paper addresses the factors that influence platform risks to help analyze P2P lending platforms. Prior research has not explored how to identify problematic P2P lending platforms in-depth and is limited by only focusing on either soft information or hard information. It identifies the characteristic factors of identifying problematic platforms and designs a P2P platform risk early warning model.

This paper aims to provide an in-depth examination of the emergent state of financial technology (fintech), particularly emphasizing capital-raising innovations and their implications for international business.

Using the highly influential articles published in fintech, the authors identify the advantages and disadvantages of each significant fintech in the credit, deposit and capital-raising services sector. The authors assess the adoption of these services and the international firm-level implications of their use.

This study highlights fintech’s role in fostering entrepreneurial internationalization, with a particular focus on the impact of crowdfunding, peer-to-peer lending and online banking. A thorough analysis of Google Scholar citations uncovers research gaps and unveils emerging trends bridging international business and fintech. Furthermore, the examination of regulatory efforts presents evidence of a robust positive relationship between global e-commerce legislation and fintech adoption, demonstrating the interconnected nature of these elements in the world of international business.

Fintech research in international business has only taken off in the last five years. Innovations and regulatory developments are continuously evolving.

This study emphasizes the significance of fintech in international business research, addressing its implications on regulatory environments, entrepreneurial internationalization and multinational corporations’ global strategies. By investigating the synergies and applications of various fintech types, the research provides valuable insights for scholars and practitioners, contributing to the advancement of knowledge in the field of international finance.

The purpose of this paper is to discuss the case-based reasoning (CBR) approach to improve microcredit initiatives by means of providing a borrower risk rating system.

The CBR approach has been used to consider the Kiva microcredit system, which provides a characterization (rating) of the risk associated with the field partner supporting the loan, but not of the specific borrower which would benefit from it. The authors discuss how the combination of available historical data on loans and their outcomes (structured as a case base) and available knowledge on how to evaluate the risk associated with a loan request can be used to provide the end users with an indication of the risk rating associated with a loan request based on similar past situations.

The adopted approach is applied and evaluated employing a selection of cases from individual loans. From this perspective, the case base and the codified knowledge about how to evaluate risks associated with a loan represent two examples of knowledge IT artifacts.

The originality of the work lies in borrower risk rating in online indirect peer-to-peer microcredit lending platforms. The case base and the codified knowledge are the two contributions in knowledge IT artifacts.

Innovation in digital technologies has been the main force in promoting growth and inclusion. However, the impact of such innovations remains ambiguous. Within this context, this study aims to analyze the distribution of digitally empowered peer-to-peer (P2P) lending in Indonesia.

This study uses a quantitative approach to estimate the impact of technological innovation in promoting economic development. In particular, this study employs empirical panel data from 135 financial technology (FinTech) companies from 2015 to 2019 and use the dynamic panel threshold regression approach. This study collects secondary data to build the estimated model.

Contrary to conventional wisdom, this study’s evidence suggests that there is a delayed effect between the contribution of P2P lending by FinTech firms on economic growth in the country. While the immense growth of FinTech seems promising, the findings indicate that FinTech is far from its optimal point. This study calculates the optimal combination between productive and consumptive lending and between Java and non-Java. In view of this finding, this study proposes strategies to effectively distribute lending and bring about the expected benefit to the economy.

Since the contribution of P2P lending on economic development has not reached its optimum, the findings expose the limitation of current technological innovation in the financial sectors. In this sense, P2P penetration on the financing market needs encouragement. The calculations for optimal allocation between productive and consumptive and between Java and non-Java provide guidance to policymakers. This study helps practitioners to shape strategy and to begin experimenting with different approaches to distribute loans effectively.

To the best of the authors’ knowledge, there are no empirical studies that examine the impact of emerging FinTech companies in promoting economic growth and financial development. The findings close this research gap, especially in regard to innovation management literature, and provide insights for practitioners, policymakers and regulators.

Global economy, growing importance of innovations as well as wide use of technologies have changed the banking business worldwide. Financial technologies (FinTech) have become an integral part of banking, and nowadays banks have started to compete beyond financial services facing increasing competition from nonfinancial institutions providing, for example, payment services. Start-up service providers, search engines, and social networks have expanded their services “interfering” in the fields traditionally covered by banks. The rapid rise of FinTech has changed the business landscape in banking asking for more innovative solutions. These recent tendencies require the banks to increase investment in FinTech, rethink service distribution channels, especially the business-to-consumers models, increase further standardization of back-office functions, etc. Some members of the financial services industry see the boom in FinTech as a threat to traditional banking industry. Others believe that FinTech has become a challenge that can be turned into an opportunity as it provides more flexibility, better functionality in some areas, and aggregation of services. The aim of the paper is to analyze the recent trends in banking, identifying opportunities and risks of FinTech for banks. A timely integration of FinTech into business allows banks to get an advantage in growing competition. This paper provides an extensive analysis of recent trends in FinTech and banking, examining experience of leading European and US banks, as well as surveys conducted among members of the financial services industry in different countries. The authors have studied the development of the financial innovation and technology market, assessed the existing practices applied in the field of FinTech, identified the main risks related to development of FinTech and financial innovations the banks are exposed to on the micro- and macrolevel. The paper provides recommendations for regulators and banks to ensure reduction of risks associated with development of FinTech. Analysis of FinTech market has shown growing competition, including from nonfinancial institutions. The paper provides practical recommendations to commercial banks for strengthening the position in financial innovations and controlling the risks associated with introduction of financial innovations.

While many believe that nonperforming loans (NPLs), privatization of banks, informal lending, and other forms of shadow-banking, as well as technological advances in machine learning for assessing creditworthiness will place China's financial regulatory system on a trajectory toward openness and privatization, other trajectories are possible and likely. Consider that each disturbance can be met with controlled alternatives. For NPLs, there are asset management companies; for informal lending, there is new technology to lower transaction costs and increase formalization and consolidation; for systemic risk presented by other forms of shadow-banking, there is systemic isolation of the traditional banking sector which substantially lowers that risk; and while machine learning promises more accurate assessments of creditworthiness for millions of individuals and small- to medium-sized enterprises, it promises far less improvement to assessments of China's 3,500 large enterprises that present substantially different variables. Privatization and openness is not necessary for China's continued development for a time just as liberalized payment regimes and foreign direct investment rules do not imply the implementation of broad, liberal capital controls. Financial regulators in China, therefore, will continue to implement policies of limited and piecemeal openness so long as the benefits of control continue to exceed those of faster-paced development.

The purpose of this study is to review the literature at the intersection of crowdfunding and gender, while examining the extent to which crowdfunding has enhanced female financial inclusion and participation.

A systematic literature review was conducted across 47 studies from 2011 to April 2021.

Most studies suggest that the likelihood of success or failure of female-led campaigns depends on external factors associated with opportunities. The study points to a general trend where although female participation has not achieved its full potential, it is greater than in other channels, while enjoying higher chances of success for female fundraisers. The study highlights gaps in the literature and the associated opportunities for future research emerging from them.

This study is the first attempt to summarise and sensitise the literature on crowdfunding and gender. The study highlights the importance of analysing the impact of context on the conceptualisation of gender in alternative finance.

The purpose of this paper is to present a systematic overview of the current state of research on innovations in financial services and identifies the areas that have received less attention, and hence offer opportunities for future research.

An extensive search identified 121 research papers that have studied innovations in financial services from January 1990 to March 2015. A thorough content analysis objectively organized and coded the studies based on various aspects including publication year, focus of study, methodology, unit of analysis, sample, data analysis method, and geographical region. Analysis of the resulting data presents an overview of the research and identifies areas for future research.

The findings indicate that research on innovations in financial services is diverse and has explored various topics. The findings summarize the research papers with regards to each of the aforementioned aspects and offer researchers directions for future research.

The sample size of 121 articles is an adequate sample size for the purpose of the study and it is in line with similar studies on innovations in other areas. However, future research can expand the study to include more academic journals in addition to reviewing and synthesizing the qualitative aspects of studies and meta-analysis of the identified relationships.

The study is the first to present a holistic overview of the current state of research on innovations in financial services. The findings offer clear directions to researchers for future research and hence can be used to promote research in these areas.