Design and Evaluation of a Fintech Platform for Small Business Lending

Thesis Abstract

Small and micro-enterprises are critical drivers of economic development and employment creation, yet access to affordable and timely financing remains a persistent challenge for their growth, particularly in regions with underdeveloped banking infrastructure. Traditional banking processes often involve lengthy credit assessments, lack of transparency, and limited technological integration, which hinder small business owners' ability to secure necessary funding swiftly. This study aims to design, implement, and evaluate a fintech-based lending platform tailored specifically for small businesses to enhance accessibility, efficiency, and transparency in the lending process. The research seeks to address the overarching question of how a technology-driven platform can improve small business borrowing experiences and outcomes. The specific objectives include (1) to develop an innovative fintech platform incorporated with alternative credit scoring algorithms and digital KYC (Know Your Customer) processes; (2) to implement the platform within a controlled operational environment; (3) to evaluate its effectiveness in terms of credit approval time, default rates, and borrower satisfaction; and (4) to identify key factors influencing platform adoption by small business owners. The study employs a mixed-methods research design integrating both qualitative and quantitative approaches to provide a comprehensive evaluation of the platform’s performance. The quantitative component involves a quasi-experimental design with a sample of 300 small business owners who access loans via the proposed fintech platform over a six-month period. Stratified random sampling ensures representation across diverse sectors such as retail, manufacturing, and services. Data collection instruments include structured questionnaires assessing user experience and satisfaction, as well as platform system logs capturing loan processing times, approval rates, and repayment performance. Validity and reliability of questionnaires are established through pilot testing and Cronbach’s alpha analysis. Quantitative data are analyzed using descriptive statistics, multiple regression analysis to identify predictor variables influencing repayment behavior, and t-tests to compare platform performance metrics against traditional lending benchmarks. Complementing this, qualitative data are gathered through semi-structured interviews with 20 small business owners and platform administrators, analyzed via thematic analysis to explore perceptions, challenges, and facilitators related to platform adoption. Ethical considerations, including informed consent, data confidentiality, and institutional review board approval, are strictly adhered to throughout the research process. Expected findings suggest that the fintech platform will significantly reduce loan approval times from an average of 10 days to under 48 hours, lower non-performing loan rates by improving credit risk assessment accuracy through alternative data sources, and increase borrower satisfaction and financial inclusion. The regression analysis is anticipated to reveal key factors such as platform usability, perceived trustworthiness, and credit assessment transparency as significant determinants of loan repayment success and user adoption. This study contributes to existing knowledge by providing empirical evidence on the effectiveness of integrated fintech solutions tailored for small business lending and identifies critical design features that influence platform success. The research extends current theoretical frameworks by adapting the Technology Acceptance Model (TAM) and Innovation Diffusion Theory (IDT) to the context of financial technology adoption among small business owners. In conclusion, the study recommends that financial service providers focus on enhancing user-centered design and leveraging alternative data analytics to improve lending efficiency. Policy implications emphasize the need for supportive regulatory frameworks that foster technological innovation in financial services. Future research directions include longitudinal studies to assess long-term impacts and scalability of fintech platforms across different regional contexts. The findings aim to guide both practitioners and policymakers in advancing inclusive finance through innovative technological solutions.