Abstract
Despite the recent expansion of digital lending platforms in developing countries, marginalized segments still face challenges in accessing credit. Many borrowers are excluded due to the absence of formal financial histories or insufficient profiles. Existing research primarily focuses on improving model accuracy and ensuring profitability rather than addressing inclusion. Hence, more inclusive digital lending systems are needed. Inclusion in this study refers to “the equitable access, distribution, and utilization of financial resources, ensuring that all societal segments, particularly underserved populations, can participate meaningfully in lending systems.” This definition emphasizes removing systemic challenges and fostering empowerment by enabling individuals to make informed decisions....
| Original language | English |
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| Awarding Institution |
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| Supervisors/Advisors |
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| Award date | 17 Nov 2025 |
| Electronic ISBNs | 978-94-6518-144-8 |
| DOIs | |
| Publication status | Published - 2025 |
Keywords
- Inclusive Lending
- Reference Architecture
- Inclusion-by-design
- Financial Inclusion Metrics
- Design Science Research
- Value-Based Requirements
- Design Principles
- Machine Learning
- Inclusive Scoring
- Hybrid Feature Penalty Tuning
- Borrower Reclassification