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Favela Fintech Adoption and Credit Access, A Field Study Design

Digital financial platforms alter capital allocation and liquidity management within informal settlements by expanding unsecured credit access. The structural interaction between automated lending algorithms and low household financial buffers generates severe vulnerability to over-indebtedness. A rigorous field evaluation architecture enables policymakers and providers to balance technological adoption with systemic consumer protection.

Objeto e sujeito

Digital financial technology platforms and credit allocation mechanisms. — The institutional, algorithmic, and behavioral determinants of fintech adoption and credit outcomes among favela residents.

Originalidade científica

Synthesizes technology acceptance paradigms with debt-layering concepts to construct a specialized field study architecture for favela economies.

Prévia do Documento

Esta é uma breve prévia. A versão completa inclui texto expandido para todas as seções, uma conclusão e uma bibliografia formatada.

Bachelor's Thesis

Degree:
Favela Fintech Adoption and Credit Access, A Field Study Design

Author:

Group

First M. Last

Advisor:

Dr. First Last

City, 2026

Contents

Approval Sheet (Folha de Aprovação)
Abstract
1.1. Context and Problem Statement
1.2. Objectives and Research Questions
1.3. Relevance and Operational Scope
2. Theoretical Foundations of Low-Income Digital Financial Inclusion
2.2. Automated Lending Mechanisms and Credit Scoring in Informal Markets
2.3. Consumption Smoothing, Indebtedness, and Structural Vulnerability
Analysis
3.1. Infrastructure Constraints and Mobile Financial Services Penetration
3.2. Evaluation of Over-Indebtedness and Platform-Driven Credit Dependence
3.3. Institutional Guardrails, Cybersecurity, and Consumer Protection
4. Methodological Framework and Field Protocol Architecture
4.1. Field Study Protocol and Ethical Evaluation Guidelines
4.2. Metric Operationalization for Credit Access and Household Resilience
Introduction
Conclusion
Bibliography

Introduction

Digital financial services have expanded rapidly across marginalized urban settlements, restructuring how informal households and micro-enterprises secure liquidity. In vulnerable communities such as favelas, financial technology platforms deliver digitized payments and unsecured microcredit where traditional banking institutions have historically maintained physical and procedural barriers [1], [4]. Consequently, digital wallets and automated credit scoring systems alter household financial management by lowering transaction frictions while embedding low-income users into alternative digital credit markets [2].

Despite increasing adoption rates, access to digital credit presents severe structural tensions. The expansion of automated digital lending frequently operates alongside existing informal borrowing channels rather than fully replacing them, compounding debt relations among economically precarious populations [3]. Moreover, disparities in digital literacy, owner education, and regional infrastructure attenuate the developmental benefits of fintech, exposing vulnerable consumers to systemic over-indebtedness, ambiguous credit ratings, and digital fraud [1], [2], [4].

To address these dynamics, this study investigates the socio-technical architecture governing fintech adoption and credit allocation within informal settlements. By evaluating technology acceptance factors, structural lending risks, and operational resilience mechanisms, the investigation conceptualizes a structured field evaluation framework [1], [5]. The resulting framework establishes operational criteria for balancing technological accessibility with rigorous consumer protection standards across urban peripheries [2], [4].

3.2. Evaluation of Over-Indebtedness and Platform-Driven Credit Dependence

The structural diffusion of mobile fintech platforms fundamentally reorganizes liquidity management across low-income informal settlements by replacing traditional collateral requirements with automated scoring models. While automated lending architectures undeniably enhance immediate credit access for historically unbanked populations (KHALID et al., 2025), they systematically transfer systemic volatility directly onto household balance sheets characterized by minimal financial reserves. Under these constraints, algorithmic credit underwriting accelerates friction-free microcredit disbursement, prompting vulnerable households to deploy digital credit lines primarily for daily consumption smoothing rather than asset accumulation (WILKIS, 2025). This operational reality demonstrates that digital financial deepening does not automatically generate sustainable economic resilience. Instead, high-frequency micro-loans paired with opaque algorithmic scoring mechanisms frequently trigger compounding repayment burdens, particularly when irregular informal earnings intersect with automated recovery systems (GLOBAL ASSESSMENT, 2026). As digital platforms embed themselves within informal economies, the accelerated velocity of unsecured credit exacerbates structural precarity among recipient households. Therefore, analyzing financial inclusion in favelas demands looking beyond aggregate onboarding metrics to rigorously evaluate platform-driven debt dependence and institutional vulnerability.

References

  1. Impact of Fintech Adoption on Operational Resilience and Financial Inclusion Among Small and Medium Enterprises in Nigeria's Informal Sector
    Abdullahi Ya’u Usman, Saidu Ibrahim Halidu, Salim Wali Mohammad
    Link DOI
  2. Exploring Fintech Integration for Credit Access Through Automated Lending and Financial Inclusion Strategies
    Ahmad Bala Naiya
    Link DOI
  3. From financial inclusion to indebtedness: How FinTech transforms credit access and household financial practices in Buenos Aires, Argentina
    Kubra M. Altaytas
    Link DOI
  4. The Impact of FinTech Adoption on Financial Inclusion: A Global Assessment of Access, Outcomes, and Emerging Risks
    Preety Chawla
  5. FINANCIAL INCLUSION THROUGH FINTECH ADOPTION: INTEGRATING FINANCIAL AND TECHNOLOGICAL PERSPECTIVES
    Dr. Endah Dewi Purnamasari, SE, MM, Emilda, Susi Handayani
  6. FinTech in Financial Inclusion: Machine Learning Applications in Assessing Credit Risk
    Majid Bazarbash
  7. A STEEP Analysis of the Fintech Adoption of the Financial Industry1
    Yeşim Şendur

Bibliografia

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Trabalho de Diploma

ABNT NBR 14724:2011 (Trabalhos acadêmicos)