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Open research questions in FinTech, Crowdfunding, Digital Finance

86 unresolved questions extracted from the limitations and future-work sections of 1,071 FinTech, Crowdfunding, Digital Finance papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • Future investigations should address these regulatory dimensions to achieve a more comprehensive understanding of the effects of digitalization over European banking customer experience. Another important note is that this study did not account for specific legislative aspects, which are critical in shaping the digitalization landscape.

    The Impact of Digitalization on Net Promoter Score (NPS) among Banking Customers in Europe · 2026 · DOI

  • 47x, predicted income increase of 28%, and business creation rates of 23 new firms per 1,000 people; however, these need to be validated by pilot implementation.

    Leveraging decentralized IoT and AIoT to revolutionize banking in developing countries: a case study of PayAll · 2026 · DOI

  • Policymakers should adopt a complementarity-oriented regulatory approach that integrates crowdfunding within broader financial systems rather than positioning it as a substitute for traditional intermediaries. Regulatory frameworks should prioritise investor protection, platform transparency, and risk disclosure, while enabling innovation through proportional oversight. Financial institutions should explore hybrid models, such as partnerships with crowdfunding platforms, to leverage distributed information and expand financing to underserved segments. Development agencies should support targeted crowdfunding initiatives in sectors with high social returns, particularly where conventional financing gaps persist.

    Crowdfunding as Financial Intermediation: A Critical Review of Its Promises, Limitations, and Economic Impact · 2026 · DOI

  • Future research should examine the demand-side implications, including how the paradigm shift affects consumer welfare, financial inclusion, and household financial decision-making. Several limitations of this study suggest directions for future research. First, our empirical analysis is limited to the 2015-2025 period, and the ecological reconstruction paradigm is still in its early stages.

    PARADIGM SHIFT IN FINTECH DEVELOPMENT IN THE AGE OF ARTIFICIAL INTELLIGENCE: FROM TOOL EMPOWERMENT TO ECOLOGICAL RECONSTRUCTION · 2026 · DOI

  • firms, regulatory bodies, and professional educators aiming to modernize accounting practices in emerging markets.

    Financial Accounting in the Digital Age: Analyzing the Impact of Technology and Automation · 2026 · DOI

  • Despite the contributions of this study, several limitations remain, and further expansion and improvement are needed. First, from a management and regulatory perspective, this study examines how digital transformation impacts corporate financial risks through internal and external supervision. Future research can expand this analysis by exploring the mechanisms of risk avoidance from a value creation perspective, such as investigating the effects of digital transformation on innovation capabilities and supply chain efficiency. Second, this study employs text analysis to measure digital transformation indicators; however, this method may be influenced by factors such as corporate characteristics and the policy environment. Therefore, future research could explore more objective and robust measures of digital transformation, such as statistical data on asset size or enterprise surveys. Third, the sample data selection in this study has certain limitations, and may not fully reflect the impact of digital transformation on corporate financial risks outside of China. Future studies could incorporate listed companies from other countries or regions with advanced digital transformation to enhance the generalizability and robustness of the findings.

    Does digital transformation reduce corporate financial risks? A dual perspective of internal disclosure and external supervision · 2026 · DOI

  • A limitation of the analysis is its focus on European countries and the use of annual data spanning 2013 to 2022. Expanding the scope of this study to cover other regions of the world would allow us to ascertain whether the identified relationships are universal or specific to Europe. In particular, including non-European emerging markets could verify whether the stronger substitution effect observed in the CEE countries also arises outside the continent. Moreover, at the time of construct- ing the dataset, several of the most recent GII indicators were not yet available, which constrained the temporal coverage and precision of some innovation measures. Subsequently, it would be use- ful to include additional control variables (e.g., interest rates and digitalisation of the financial sec- tor), as well as results obtained from BIS (Bank of International Settlements) research (Cornelli et al. 2021), analysing how mergers and acquisitions by large banks and large technology compa- nies (BigTechs) affect fintech investment. This would offer a broader perspective and provide bet- ter insights for policymakers, investors, and the fintech sector itself.

    Determinants of Fintech Fundraising in Europe · 2026 · DOI

  • Future research could extend this analysis in several directions. First, incorporating broader economic and sustainability-related aspects would align with recent studies that view fintech and related digital innovations through the lens of sustainable development, sectoral structure, and macro-financial performance (Barua et al. 2025; Golder and Barua 2025). Second, it could focus more explicitly on financing technology transfer from universities and public research institutes, including the role of university spin-offs, technology transfer offices, and public–private partnership schemes. This would build on existing literature on barriers to university technology transfer and entrepreneurial ecosystems (Van Roy and Nepelski 2017; Quiñones et al. 2020; Trinugroho et al. 2021). Third, combining firm- and deal-level data on fintech fundraising with regional indicators of knowledge creation and trust in incumbent financial institutions could reveal the micro-level mechanisms behind the country-level patterns documented in this study (Cojoianu et al. 2023). Finally, qualitative research, such as interviews with investors, fintech founders, and regulators in CEE and Western Europe, could provide further insight into how perceived regulatory risk, human capital constraints, and market structure influence strategic decisions regarding fintech investment and expansion (Ruhland and Wiese 2023; Panday, Nyawo, and Vilakazi 2024).

    Determinants of Fintech Fundraising in Europe · 2026 · DOI

  • Measuring and Monitoring Inclusive Growth: Multiple Definitions, Open Questions, and Some Constructive Proposals (ADB Sustainable Development Working Paper No.

    Branchless Banking and Inclusive Growth: Comparative Evidence from European Emerging Economies · 2026 · DOI

  • Given the thorough examination of the FinTech ecosystem, and the vulnerabilities identified at user, platform, and institutional levels, the following recommendations are proposed: Consumer Preparedness and Behavioral Resilience: Practical Capability Building: The authorities and financial institutions must not restrict themselves to generic Multidimensional Preparedness: Consumer preparedness should refer to awareness of risk, active protection • awareness slogans but rather focus more on practical capability building. • practices, and post fraud event response and should consist of three-dimensional capabilities. • Response Habit Formation: Training should focus on cultivating habits that will help in minimizing the ‘golden hour’. Such habits include first reporting the matter immediately, freezing the transaction, and escalating the issue formally.

    An Analytical Study of FinTech Frauds in India: Types, Trends, and Ecosystem Vulnerabilities · 2026 · DOI

  • This research has several limitations that need to be considered in drawing conclusions and developing further research. First, the observation period only covers 2015 to 2024, so the results of the study are not fully able to describe the long-term impact of banking financial performance. digitalization on Digital transformation in the banking sector is a gradual process whose effects tend to appear in the medium to long term. Second, this study only used nine samples of conventional banks from the BUKU III and BUKU IV categories that have digital services. The relatively limited number of samples can reduce the ability to generalize research results to the entire banking industry in Indonesia. For smaller-scale banks or Islamic banks may have different characteristics in the implementation of digitalization. Third, this study fully uses secondary data sourced from the annual report, the official website of the Financial Services Authority (OJK), and the Indonesia Stock Exchange (IDX). Reliance on secondary data poses a potential limitation of accuracy Digital Banking Adoption...– Putri, Febriyani, Adriyanto 105 because it depends on the completeness and reliability of each bank's reporting. transactions, digital Fourth, the empirical model used only focuses on three main variables, namely total digital transaction growth, and speed of digital adoption, without considering other external factors such as national digital infrastructure, digital financial literacy level, and government regulatory support. These factors have the potential to have an additional influence on the bank's financial performance but have not been accommodated in this study. Finally, the results of the analysis show that most independent variables do not have a significant effect on profitability (ROA). This indicates the possibility of mediation or moderation variables that have not been included, such as operational efficiency, the level of interbank competition, or the level of customer trust in digital services. Therefore, further research is expected to expand the model by including these variables to gain a more comprehensive understanding of the influence of digitalization on banking financial performance in Indonesia. REFERENCES Adel, N. (2024).

    DIGITAL BANKING ADOPTION AND FINANCIAL PERFORMANCE: EMPIRICAL EVIDENCE IN INDONESIA · 2026 · DOI

  • This research is subject to specific limitations that warrant consideration during the interpretation of its findings. Firstly, the adoption of a cross-sectional research design precludes the capture of dynamic temporal shifts in students' financial behavior. Consequently, the implementation of a longitudinal approach is recommended for subsequent investigations to facilitate a comprehensive understanding of financial behavior's developmental trajectory. Second, the respondents in this study were limited to undergraduate students in Indonesia, so the results cannot be broadly generalized to all groups, such as workers, business owners, or other age groups. The characteristics of college students as a digital generation may also influence how they utilize fintech, so research in other populations is needed to test the consistency of the findings. Third, this study solely employed perceived usefulness of fintech as the mediating variable, thereby not incorporating other potential factors that may affect the relationship among variables, such as risk perception, financial attitudes, or self-control. The 386 International Journal of Accounting and Finance in Asia Pacific (IJAFAP) Vol. 9 No. 2, pp.373-390, June, 2026 E-ISSN: 2684-9763 P-ISSN: 2655-6502 https://www.ejournal.aibpmjournals.com/index.php/IJAFAP inclusion of these variables in future studies is anticipated to yield a broader understanding of financial behavior. Fourth, the variables measured in this research utilized a questionnaire designed to capture respondents’ perceptions, which has the potential to introduce subjective biases, such as self-reporting bias. Respondents may provide answers that are considered most socially appropriate (social desirability bias), thus not fully reflecting the actual state of financial behavior. ACKNOWLEDGMENT Profound gratitude is extended to all undergraduate students in Indonesia who participated in this study. Gratitude is also extended to the Faculty of Economics and Business, particularly the Management program, for their invaluable guidance and academic support throughout the research undertaking. Finally, profound indebtedness is conveyed to all individuals who, directly or indirectly, facilitated the successful culmination of this research and the subsequent preparation of this scientific manuscript. DECLARATION OF CONFLICTING INTERESTS The authors hereby affirm the absence of any conflicts of interest pertinent to the publication of this article. This investigation was conducted autonomously, devoid of any commercial or financial affiliations that could potentially have influenced the reported findings. REFERENCES Algarni, M. A., Ali, M., & Ali, I. (2024).

    Antecedents of Financial Management Behavior among Indonesian University Students: The Mediating Role of Perceived Usefulness of Fintech · 2026 · DOI

  • Agentic conversational agents (CAs) are rapidly diffusing in regional banking, yet their implications for digital transformation (DT) remain poorly understood.

    Conversational Agent-Driven Digital Transformation In Regional Banking · 2026

  • Mitigation Strategy Robust encryption of financial data (e.g., income, assets 𝑎, risk tolerance 𝑟); strict access controls; continuous security monitoring and threat detection. Implement multi-factor authentication; regularly update security protocols; conduct penetration testing; incident response plan. Develop transparent data usage policies; obtain explicit user consent for data collection and processing; establish data subject rights processes (e.g., right to access, right to be forgotten). Employ fairness-aware AI algorithms; regularly audit AI models for bias; use diverse training datasets; establish explainability and interpretability of AI decisions; independent ethics review board. Improve transparency in AI decision-making processes; provide clear explanations of investment recommendations; offer human advisor oversight to provide reassurance and address user concerns.

    Research on Personalized Asset Allocation Using AI Agents in Robo-Advisory Scenarios · 2026 · DOI

  • 6.1. Emerging Trends in AI and Robo-Advisory The future of robo-advisory is inextricably linked to advancements in artificial intelligence. Federated learning, enabling model training across decentralized datasets without direct data sharing, promises enhanced personalization while preserving user privacy. Explainable AI (XAI) is crucial for building trust and ensuring regulatory compliance by providing transparent justifications for algorithmic recommendations. 174 Vol. 3 No. 2 (2026) Journal of Computer, Signal, and System Research Furthermore, the integration of alternative data sources, such as social media sentiment and macroeconomic indicators ( 𝑥𝑖 ), can improve predictive accuracy and risk management. These trends collectively suggest a future where robo-advisors are more personalized, transparent, and robust, offering sophisticated financial advice accessible to a wider audience. 6.2. The Future of Personalized Investment The future of personalized investment envisions AI agents evolving into proactive financial partners. Hyper-personalization will become the norm, with algorithms deeply understanding individual risk tolerance, financial goals, and even psychological biases. Investment strategies will dynamically adapt to life events, market fluctuations, and evolving preferences, moving beyond static risk profiles. AI agents will anticipate future needs, proactively suggesting adjustments to asset allocations and financial plans. Imagine a system that not only manages investments but also optimizes spending, debt management, and individual’s unique insurance coverage, all tailored to the circumstances and maximizing their long-term financial well-being [12].

    Research on Personalized Asset Allocation Using AI Agents in Robo-Advisory Scenarios · 2026 · DOI

  • on FinTech-driven digital transformation. 8 Sachin Kumar Small Businesses and The study showed that peer-to- Explains how FinTech IJFMR260378263 Volume 8, Issue 3, May-June 2026 3 International Journal for Multidisciplinary Research (IJFMR) E-ISSN: 2582-2160 ● Website: www.ijfmr.com ● Email: [email protected] Sharma et al.

    The Impact of Fintech on Business Operations and the Financial Services Industry · 2026 · DOI

  • The paper identifies that contextual integrity standards for data collection are routinely exceeded through backgrounded SDK and API processes that repurpose data beyond original intent, yet provides no framework for assessing what level of transparency or consent mechanisms would be required to bring SMS scraping and third-party data access practices into legal and ethical compliance with Kenya's Data Protection Act.

    Risk, Data, Alignment: Making Credit Scoring Work in Kenya · 2026 · DOI

  • The study documents that features are engineered to capture psychological and sociological aspects (e.g., saving money behavior, sports betting participation) from dynamic transaction data, but the authors acknowledge that some assumed correlations with creditworthiness do not hold empirically. No methodology is provided for systematically testing whether these behavioral proxies transfer across different cultural and economic contexts within Kenya.

    Risk, Data, Alignment: Making Credit Scoring Work in Kenya · 2026 · DOI

  • The paper argues that modeling uncertainty in credit scoring systems involves assumptions about the relationship between risk and prediction that can amplify rather than mitigate risks, yet does not empirically measure whether credit scoring models trained on alternative data in Kenya systematically over-estimate or under-estimate default rates for specific borrower subpopulations (e.g., by income level, geography, or industry sector).

    Risk, Data, Alignment: Making Credit Scoring Work in Kenya · 2026 · DOI

  • The research identifies infrastructural dependency gaps where large data holders like Safaricom cannot leverage fragmented data repositories in predictive models due to prohibitively high transformation costs, but provides no cost-benefit analysis or technical specification of what data integration and transformation infrastructure would be required to make alternative data operationalized at scale across Kenyan digital lenders.

    Risk, Data, Alignment: Making Credit Scoring Work in Kenya · 2026 · DOI

  • The paper shows that data science teams reduce hundreds or thousands of engineered features to 10-20 final features using correlation analysis, but the authors note that proprietary and secret feature selection techniques emerge from non-scalable manual checks where correlation assumptions fail. There is no systematic methodology documented for replicating or validating these manual corrections across different fintech startups or geographic contexts in Kenya.

    Risk, Data, Alignment: Making Credit Scoring Work in Kenya · 2026 · DOI

  • The study identifies that phone sharing practices in rural and low-income urban Kenya are systematically classified as risk signals through device ID individualization in credit scoring models, yet lacks empirical validation of whether social phone-sharing norms actually predict loan default differently than the models assume, or whether model predictions change when cultural practices are explicitly incorporated as features.

    Risk, Data, Alignment: Making Credit Scoring Work in Kenya · 2026 · DOI

  • The paper documents SMS scraping and third-party API access practices for alternative data collection in credit scoring, but provides no empirical analysis of how frequently SIM card fungibility causes data profile mixing and credit record misattribution across borrowers in the Kenyan CRB system. Quantifying the actual error rates and borrower impact of this infrastructural dependency gap would inform regulatory design.

    Risk, Data, Alignment: Making Credit Scoring Work in Kenya · 2026 · DOI

  • The paper establishes that algorithmic fairness and explainability positively influence financial inclusion through trust (AF→FI = 0.296, EA→FI = 0.255) but provides no longitudinal framework to measure whether these effects persist after algorithm retraining cycles or when training data distributions shift due to changing economic conditions in developing economies.

    A Machine Learning Perspective on FinTech-Driven Inclusion: Addressing Algorithm Bias in Credit Scoring Systems in Developing Economies · 2026 · DOI

  • The bootstrap mediation analysis (5,000 resamples) validates partial mediation effects for perceived trust but does not specify how the fairness-explainability-trust-inclusion model should scale when integrated into multi-stakeholder FinTech ecosystems with competing priorities among lenders, regulators, and underserved borrowers in developing economies.

    A Machine Learning Perspective on FinTech-Driven Inclusion: Addressing Algorithm Bias in Credit Scoring Systems in Developing Economies · 2026 · DOI

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86 open questions have been extracted from the limitations and future-work passages of 1,071 FinTech, Crowdfunding, Digital Finance papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

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