Peer-to-peer lending, hereafter P2P lending, is one of the most visible forms of fintech-enabled credit intermediation. In its basic form, a digital platform connects borrowers who seek credit with lenders or investors willing to provide funds. The platform does not operate like a conventional deposit-taking bank; instead, it designs the marketplace, screens borrowers, communicates risk, sets or facilitates pricing, distributes repayments, and often applies data analytics to support credit decisions. This platform-based architecture gives P2P lending strategic importance for business management because it changes how credit is originated, how trust is produced, how risks are priced, and how financial access is governed.
The early promise of P2P lending was strongly associated with democratized finance. Zopa presented itself as the first peer-to-peer lending company in 2005, and subsequent platforms in the United States, Europe, China, and emerging economies positioned the model as a faster, lower-cost, and more inclusive alternative to traditional banking. In Indonesia, the financial regulator describes fintech lending or P2P lending as a digital financial service that brings together lenders and borrowers to enter loan agreements directly through an electronic system (Otoritas Jasa Keuangan [OJK], n.d.). This definition illustrates the institutional relevance of P2P lending in markets where bank credit can be difficult to access, especially for consumers, microenterprises, and small and medium enterprises (SMEs).
Scholarly attention to P2P lending has expanded because the phenomenon sits at the intersection of several research domains. Finance scholars investigate default risk, loan pricing, investor return, screening, credit scoring, and information asymmetry. Information systems scholars study platform trust, data-driven decision making, online reputation, interface design, and algorithmic credit assessment. Marketing and consumer behavior scholars investigate borrower narratives, persuasion, social influence, and investor decision heuristics. Entrepreneurship and development scholars examine whether P2P lending improves SME access to finance and whether it can serve underserved borrowers in economies where bank branch penetration is limited. Legal and policy scholars focus on regulation, data privacy, illegal lending, collection ethics, and consumer protection.
A broad and rapidly expanding literature creates both opportunity and difficulty. Opportunity arises because researchers now have enough publications to identify major intellectual structures. Difficulty arises because the literature is fragmented across journals, methods, countries, and disciplinary vocabularies. Terms such as P2P lending, crowdlending, marketplace lending, online lending, debt crowdfunding, and fintech lending often refer to overlapping but not always identical phenomena. As a result, individual studies may make valuable contributions while the overall structure of the field remains difficult to interpret. Bibliometric analysis is useful in this situation because it systematically maps publication growth, influential outlets, country collaboration, citation structures, and keyword relationships (Donthu et al., 2021; Zupic & Čater, 2015).
Previous bibliometric work has already shown that P2P lending has become a substantial field. Kholidah et al. (2022) mapped P2P lending literature from an economics and business perspective using Scopus and VOSviewer. Ribeiro-Navarrete et al. (2022) mapped crowdlending research through keyword co-occurrence, co-citation, and bibliographic coupling, finding that the field combines financial and behavioral finance themes and increasingly moves toward technology-based innovation. Rabbani et al. (2022) reviewed crowdfunding and P2P lending research using bibliometric and meta-analytic methods. More recently, Ikhlash and Sembiring (2026) reported a Scopus-based bibliometric dataset of 833 documents from 2007 to 2024, documenting the field's growth, source structure, and international collaboration patterns. These studies provide a strong basis for a synthesized bibliometric review that connects performance indicators with research themes and future scholarly priorities.
The present manuscript therefore asks four research questions. First, how has P2P lending research evolved in terms of publication growth and phases of development? Second, which sources, countries, and collaboration networks shape the field? Third, what major thematic clusters define P2P lending research? Fourth, which future research directions are most promising for high-quality management, finance, information systems, and policy scholarship? By answering these questions, the article contributes a structured map of P2P lending research and translates bibliometric patterns into a research agenda.

2.1. P2P Lending as Platform-Based Credit Intermediation
P2P lending can be understood as a two-sided or multi-sided platform model in which borrowers and lenders meet through a digital intermediary. The platform reduces search and transaction costs, but it also creates new problems of trust and risk allocation. Unlike a bank, which usually keeps loans on its balance sheet and applies internal underwriting, a P2P platform often distributes credit risk to lenders or investors. This distinction makes borrower screening, information disclosure, and investor decision quality central concerns. Serrano-Cinca et al. (2015) emphasized that individual investors bear credit risk in P2P lending and face information asymmetry when evaluating borrowers. Iyer et al. (2016) further showed that peer lenders can use soft information to infer borrower quality, highlighting the distinctive information environment of online credit markets.
Trust is one of the earliest and most enduring topics in P2P lending research. Chen et al. (2014) developed a lender-side trust model for online P2P lending, showing that lender decisions are influenced not only by formal credit information but also by trust-building platform mechanisms. Borrower narratives also matter. Herzenstein et al. (2011) showed that unverifiable information in borrower stories can influence lending decisions beyond objective financial variables. Dorfleitner et al. (2016) extended this soft-information literature by examining how description-text factors relate to funding probability and default probability. These studies helped establish P2P lending as a setting where financial decisions are socially and linguistically mediated.
2.2. From Credit Access to Risk and Regulation
The second major research stream concerns the balance between financial inclusion and risk. P2P lending can provide credit to consumers and firms underserved by banks. Oh and Rosenkranz (2020) found that financial institution efficiency, financial literacy, lower branch and ATM penetration, information technology infrastructure, and new business density are relevant to P2P lending expansion across economies. Abbasi et al. (2021) linked P2P fintechs to SME access to finance, while Coakley and Huang (2023) examined P2P lending as a form of outside entrepreneurial finance. These studies position P2P lending as a possible inclusion mechanism rather than only a consumer-credit product.
Yet inclusion benefits are inseparable from governance challenges. Platform lending can produce overborrowing, weak borrower screening, predatory collection, misuse of personal data, and instability when regulation lags behind innovation. In Indonesia, Suryono et al. (2021) identified issues such as public understanding, data leakage, illegal fintech lending, personal data fraud, and marketing ethics. These issues illustrate why bibliometric research should not simply celebrate publication growth or technological innovation. A high-quality research agenda must also examine institutional safeguards, consumer welfare, responsible innovation, and the social consequences of digital credit.

This study uses a bibliometric review design. Bibliometric analysis is appropriate when a research area has accumulated enough publications to permit systematic mapping of performance indicators and intellectual structures. The approach differs from a traditional narrative review because it uses quantitative publication metadata, including year, source, author, country, citation, and keyword information. It also differs from a meta-analysis because it does not aggregate statistical effect sizes from comparable empirical tests. Instead, it maps the structure and evolution of a research field (Aria & Cuccurullo, 2017; Donthu et al., 2021; Zupic & Čater, 2015).
The empirical base of this manuscript is a secondary bibliometric synthesis. The main numerical indicators are drawn from published Scopus-based bibliometric evidence, especially the 2007-2024 dataset reported by Ikhlash and Sembiring (2026), which included 833 documents from 472 sources. This secondary approach is transparent and appropriate for an integrative manuscript whose objective is to consolidate bibliometric findings, identify thematic patterns, and formulate future research questions. It should be interpreted as a synthesis of available bibliometric evidence rather than a new proprietary Scopus export. To strengthen interpretation, the manuscript also draws on major P2P lending studies and established bibliometric-method references.
The analysis followed four stages. First, the scope of the review was defined around P2P lending, crowdlending, online lending, marketplace lending, and fintech lending. Second, bibliometric performance indicators were summarized, including publication growth, source productivity, document types, author collaboration, and country collaboration. Third, science-mapping evidence from prior bibliometric studies was interpreted to identify thematic clusters. Fourth, the results were translated into a future research agenda for management, finance, information systems, and policy scholarship. Table 1 summarizes the review design.
Table 1. Bibliometric Review Design and Analytical Decisions

4.1. Performance Profile of P2P Lending Research
The bibliometric profile indicates that P2P lending has become a substantial research field. The synthesized Scopus-based dataset reported by Ikhlash and Sembiring (2026) covered 833 documents from 472 sources between 2007 and 2024. The annual growth rate was 23.86%, and the average citation per document was 21.4. The corpus included 1,624 authors, 2,056 author keywords, and an international co-authorship rate of 26.89%. Most documents were journal articles, followed by conference papers and conference reviews. Table 2 presents the key profile indicators.
These in Table 2 indicators reveal two important points. First, P2P lending research is broad, not concentrated in a small number of sources or authors. The 472 sources show that the topic cuts across finance, information systems, e-commerce, operations, entrepreneurship, sustainability, and law. Second, the authorship profile suggests collaborative research but not a fully globalized knowledge network. A co-authors-per-document score of 2.81 reflects moderate collaboration, while international co-authorship below one-third suggests room for more cross-country comparative work. This matters because P2P lending outcomes are highly institution-dependent; platform risk, regulation, borrower protection, investor behavior, and default dynamics differ across legal and market contexts.
Table 2. Main Bibliometric Profile of P2P Lending Research, 2007-2024

4.2. Publication Growth and Development Phases
The annual publication trend shows a clear movement from emergence to acceleration and consolidation. In the earliest period, from 2007 to 2014, publication volume was small. Research focused on the novelty of online lending platforms, the credibility of borrowers, the role of soft information, and the basic economics of disintermediation. Growth became visible after 2015, when publication counts rose from 29 in 2015 to 67 in 2019. This acceleration coincided with the increasing availability of platform data, growing use of LendingClub-type datasets, and wider interest in fintech as a business and policy phenomenon.
The strongest publication period occurred around 2020 and 2021, with 124 and 132 documents respectively. This peak reflects the maturation of P2P lending as a research field and the broader expansion of digital finance research during and after the COVID-19 period. Publications remained high in 2022 and 2023, with 114 and 124 documents. The 2024 number in the synthesized dataset is lower, but this should be interpreted cautiously because bibliometric database coverage for the most recent year is often incomplete at the date of retrieval. Table 3 displays annual scientific production.
Table 3. Annual Scientific Production in P2P Lending Research

4.3. Source Productivity and Disciplinary Location
The most relevant sources show that P2P lending is not confined to one disciplinary home. Finance Research Letters is the most productive outlet in the synthesized dataset, followed by Electronic Commerce Research and Applications and Financial Innovation. This distribution confirms the hybrid nature of the field. Finance outlets publish work on default risk, loan pricing, investor returns, platform economics, and macro-financial implications. E-commerce and information systems outlets publish work on platform trust, digital signals, online behavior, and data analytics. Sustainability and operations outlets indicate that P2P lending has also entered debates about SME finance, supply chains, and sustainable business models.
A managerial implication follows from this source distribution. P2P lending research should not be evaluated only through conventional finance categories. It is a platform economy topic as much as a credit topic. High-quality studies can therefore make contributions by combining credit-risk modeling with platform governance, behavioral decision theory, technology ethics, and institutional analysis. Table 4 lists the ten most productive sources reported in the synthesized Scopus-based dataset.
Table 4. Most Relevant Sources in P2P Lending Research

4.4. Geographical and Collaboration Structure
Country production is dominated by China and the United States, with Indonesia also appearing prominently in the available bibliometric evidence. Ikhlash and Sembiring (2026) reported China as the leading country by article frequency, followed by the United States and Indonesia. This pattern reflects market reality and data availability. China and the United States generated large P2P lending markets and extensive platform data, enabling researchers to analyze funding success, default risk, borrower characteristics, social information, and platform failure. Indonesia's presence reflects the relevance of fintech lending for financial inclusion, consumer protection, and digital finance regulation in emerging economies.
Country collaboration patterns show that China-United States collaboration is the strongest dyad in the synthesized dataset, followed by China-Hong Kong and China-United Kingdom ties. The collaboration table also shows Singapore, France, Korea, Australia, and Japan as network partners. This structure suggests that P2P lending research is shaped by a limited number of cross-border knowledge corridors. More collaboration between advanced and emerging economies would improve theoretical generalization because platform lending develops differently under different rules, credit cultures, data infrastructures, and consumer-protection systems. Table 5 summarizes the leading collaboration pairs.
Table 5. Leading International Collaboration Pairs in P2P Lending Research

4.5. Thematic Structure of P2P Lending Research
The thematic structure of the field can be organized into five clusters. The first cluster concerns information asymmetry, trust, and soft information. This cluster is foundational because P2P lending markets require lenders to assess borrower quality without the full monitoring capacity of banks. The second cluster concerns credit risk and predictive analytics. This stream has moved from logistic regression, survival analysis, and traditional credit scoring toward machine learning and hybrid models that use structured and unstructured data. The third cluster concerns financial inclusion, SME finance, and entrepreneurship. This stream asks whether P2P lending fills credit gaps and supports productive activity. The fourth cluster concerns regulation, platform governance, and consumer protection. This stream becomes more important as P2P lending scales and as illegal lending, data privacy, and collection practices become public concerns. The fifth cluster concerns sustainability, Islamic finance, and social-impact lending. This stream is emerging but strategically important because it connects digital credit with social responsibility and alternative institutional designs.
The clusters should not be treated as isolated. For example, machine learning research depends on information asymmetry problems, while regulation depends on how platforms collect, interpret, and disclose borrower information. Financial inclusion studies must also address consumer protection because credit access without responsible lending can create harm. Likewise, sustainability research must engage default risk because social-impact lending cannot be sustainable if platform models misprice risk. Table 6 presents the thematic map and future research agenda.

Table 6. Thematic Clusters and Future Research Agenda

5.1. From Novelty to Infrastructure
The bibliometric evidence suggests that P2P lending research has passed through a transition from novelty to infrastructure. Early studies treated P2P lending as an innovative online marketplace that challenged bank intermediation. Research questions focused on why lenders fund particular borrowers, how borrower narratives persuade investors, and whether nonexpert lenders can process soft information. As the field matured, scholars began to examine platform credit risk, default prediction, machine learning, and market outcomes. More recent studies increasingly connect P2P lending to financial inclusion, SME finance, regulation, and sustainability. This trajectory mirrors the development of fintech itself: a phenomenon initially celebrated for disruption becomes a mainstream object of governance, risk management, and institutional design.
This transition has implications for theory. P2P lending cannot be fully explained by banking theory alone because platforms do not simply replicate bank intermediation. Nor can it be explained by e-commerce theory alone because credit risk, regulation, and repayment obligations make lending different from ordinary digital transactions. P2P lending is better understood as platform-based credit intermediation, a hybrid domain where financial economics, information systems, behavioral decision making, and institutional theory intersect. Bibliometric evidence supports this view because the most productive sources include finance, e-commerce, financial innovation, operational research, information systems, and sustainability journals.
5.2. Knowledge Gaps and Theoretical Opportunities
A first knowledge gap concerns causality. Many P2P lending studies use observational platform data to predict funding success or default. These studies are valuable, but they often struggle to distinguish correlation from causal impact. Future research should use quasi-experimental designs, natural experiments, regulatory changes, platform rule changes, and longitudinal borrower data to assess whether P2P lending improves financial outcomes or simply reallocates credit to borrowers already likely to obtain funds elsewhere. This is especially important for inclusion-oriented claims. The fact that a platform reaches underserved borrowers does not automatically prove that it improves welfare. Borrower outcomes such as income stability, business survival, household resilience, and debt stress need direct measurement.
A second knowledge gap concerns model governance. Machine learning has become a central direction in credit-risk research, but prediction accuracy is not the only managerial or policy criterion. A highly accurate model may still be unfair, opaque, unstable across economic cycles, or difficult for regulators to audit. Future research should therefore integrate credit scoring with explainability, fairness, adverse impact, data minimization, and human accountability. For managers, this means that algorithmic credit assessment should be governed as a strategic risk system, not merely as a technical tool. For scholars, it opens opportunities to connect fintech lending with responsible artificial intelligence and digital ethics.
A third gap concerns lender welfare. P2P lending research often focuses on borrower access or platform growth, but lenders also face risks. In many models, lenders bear default risk while platforms earn fees from origination, servicing, or transaction volume. This creates potential incentive misalignment. Future studies should examine whether lenders understand risk, how platforms communicate expected returns and losses, and whether investor protection rules change behavior. Research on lender learning, diversification, risk disclosure, and behavioral biases would contribute to both finance and consumer-protection scholarship.
A fourth gap concerns emerging-market institutional diversity. The field is dominated by China and the United States, with growing evidence from countries such as Indonesia. However, P2P lending in emerging markets may differ fundamentally from P2P lending in advanced markets because of differences in financial literacy, bank access, informal credit traditions, data infrastructure, consumer protection, enforcement capacity, and religious-finance institutions. Comparative research can reveal whether findings from large platform datasets generalize to markets where borrowers may be more vulnerable and regulation may be evolving.
5.3. Implications for Management, Policy, and Education
For platform managers, the review highlights the need to treat trust as a core asset. Trust is built not only through user acquisition and branding but also through accurate risk disclosure, fair collection practices, responsible data use, complaint resolution, and transparent communication. Platforms that emphasize loan volume while neglecting borrower welfare, lender risk, or data protection may face reputational damage and regulatory sanctions. The research agenda therefore aligns with stakeholder-oriented management: borrowers, lenders, regulators, merchants, communities, and platform owners all affect long-term viability.
For regulators, the bibliometric map suggests that policy should be evidence-based and adaptive. P2P lending can support financial inclusion and SME finance, but weak oversight can produce illegal lending, data misuse, coercive collection, and systemic reputational harm to fintech. Regulatory analysis should therefore move beyond licensing counts toward outcome-based monitoring. Useful indicators include repeat borrowing, default concentration, lender loss distribution, complaint rates, loan purpose, borrower demographics, platform capital adequacy, and the transparency of risk models. Cross-country learning is important because regulatory regimes differ in whether they treat P2P lending primarily as credit, investment, crowdfunding, marketplace finance, or fintech lending.
For universities and management educators, P2P lending provides a rich teaching case. It combines digital business models, platform strategy, financial management, consumer behavior, data analytics, ethics, and public policy. Students can analyze how platforms create value, how they price risk, how incentives may misalign, and how responsible innovation can be designed. In emerging economies, P2P lending can also be connected to entrepreneurship education, financial inclusion, Islamic finance, and SME development. This interdisciplinary teaching value reflects the same hybridity observed in the bibliometric source structure.
For researchers, the review supports a more integrative approach. Future articles should not simply add another default-prediction model unless they explain what new theory, data, or managerial insight the model provides. Similarly, studies on adoption should move beyond intention and perceived usefulness to examine actual repayment behavior, debt stress, and platform accountability. High-impact research will likely emerge from studies that connect micro-level behavior with platform-level design and macro-level regulation.
5.4. Future Research Agenda
The bibliometric map also allows a more specific research agenda. First, future studies should examine borrower welfare after P2P lending participation. Most platform datasets record loan-level variables, funding outcomes, and repayment status, but they rarely show whether the borrower becomes financially healthier. A consumer borrower may repay successfully while experiencing stress, reduced consumption of necessities, or dependence on repeat borrowing. An SME borrower may obtain working capital but still face unstable revenue or declining margins. Research that links platform records with survey, tax, business-performance, or household-finance data would produce stronger evidence about the real economic value of P2P lending.
Second, scholars should study platform incentives more directly. Many platforms earn revenue from origination, servicing, or transaction fees, while lenders and borrowers carry much of the economic risk. This creates the possibility that platform growth objectives may conflict with responsible lending or investor protection. Management research can contribute by examining governance mechanisms that align incentives, such as risk-retention rules, transparent fee structures, lender loss disclosure, loan performance dashboards, and independent audits of credit models. Such studies would connect fintech strategy with corporate governance and stakeholder theory.
Third, the rise of artificial intelligence requires a new generation of credit-risk research. Future models should be evaluated not only by area under the curve, precision, recall, or default classification but also by interpretability, fairness, portability across markets, and resistance to economic shocks. A model trained on one platform or country may fail when applied to another institutional setting. Researchers should therefore test external validity, monitor model drift, and examine whether algorithmic lending produces discriminatory outcomes for particular income, gender, age, regional, or religious groups.
Fourth, comparative regulatory research is needed. P2P lending regulation differs across jurisdictions in licensing requirements, capital rules, permissible guarantees, investor protection, data access, collection practices, and credit reporting. These differences create natural laboratories for studying how policy shapes platform behavior and user outcomes. Cross-country research can identify whether strict regulation reduces innovation, whether weak regulation increases consumer harm, and which balanced regimes support both inclusion and trust.
Fifth, future bibliometric studies should become more reproducible. Researchers should publish search strings, database dates, inclusion criteria, deduplication procedures, thesaurus files, and analysis code. They should also compare Scopus, Web of Science, OpenAlex, Dimensions, and Google Scholar coverage where possible. Because the field uses multiple terms, multilingual and regional searches are important. Indonesian, Chinese, Spanish, Arabic, and Islamic-finance terminology may reveal literature that is underrepresented in English-only searches. Table 7 summarizes agenda themes that can support future high-quality articles.

Table 7. Priority Agenda for Future P2P Lending Research

5.5. Limitations
This manuscript has limitations. First, it is a secondary bibliometric synthesis rather than a fresh raw export from Scopus, Web of Science, OpenAlex, or Dimensions. The numerical indicators therefore depend on the search strings, indexing decisions, and data-cleaning procedures of the cited bibliometric studies. Second, the 2024 publication count should be treated cautiously because recent-year indexing is often incomplete. Third, bibliometric indicators measure visibility and structure, not necessarily research quality or social impact. A frequently cited paper may be influential, but citation counts do not automatically indicate methodological rigor, policy relevance, or ethical value. Fourth, P2P lending terminology varies across regions, so some relevant studies using terms such as digital lending, online loans, marketplace credit, fintech lending, or debt crowdfunding may be excluded from narrow search strategies. These limitations create opportunities for future research using transparent database exports, reproducible scripts, and multilingual search strategies.

This bibliometric review mapped the development, structure, and future agenda of P2P lending research. The field has grown from a small stream of early online lending studies into a multidisciplinary domain that spans finance, information systems, e-commerce, operations, entrepreneurship, sustainability, and policy. Publication growth accelerated after 2015 and peaked around 2020-2021, while recent research shows consolidation around risk analytics, platform governance, inclusion, and sustainability. The most productive sources confirm the hybrid nature of the topic, and collaboration patterns show strong China-United States influence with growing relevance for emerging economies such as Indonesia.
The thematic synthesis identified five major clusters: information asymmetry and trust, credit risk and machine learning, financial inclusion and SME finance, regulation and platform governance, and sustainability or Islamic P2P lending. The central message is that P2P lending research should move beyond the early question of whether digital platforms can connect borrowers and lenders. The more important questions now concern how these platforms should be governed, how risks should be disclosed and predicted, how borrower and lender welfare should be protected, and whether P2P lending contributes to inclusive and sustainable economic development.
For management scholars, P2P lending is a valuable site for studying platform strategy, responsible innovation, algorithmic governance, and stakeholder trust. For finance scholars, it remains a rich context for testing theories of information asymmetry, credit risk, and investor behavior. For policymakers, the literature demonstrates that innovation and protection must be designed together. The next generation of P2P lending research will be most valuable when it integrates rigorous empirical methods, transparent bibliometric mapping, ethical platform design, and measurable social outcomes.