This paper explores the dual impact of digital banks and alternative lenders
on financial inclusion and the regulatory challenges posed by their business
models. It discusses the integration of digital platforms, machine learning
(ML), and Large Language Models (LLMs) in enhancing financial services
accessibility for underserved populations. Through a detailed analysis of
operational frameworks and technological infrastructures, this research
identifies key mechanisms that facilitate broader financial access and mitigate
traditional barriers. Additionally, the paper addresses significant regulatory
concerns involving data privacy, algorithmic bias, financial stability, and
consumer protection. Employing a mixed-methods approach, which combines
quantitative financial data analysis with qualitative insights from industry
experts, this paper elucidates the complexities of leveraging digital
technology to foster financial inclusivity. The findings underscore the
necessity of evolving regulatory frameworks that harmonize innovation with
comprehensive risk management. This paper concludes with policy recommendations
for regulators, financial institutions, and technology providers, aiming to
cultivate a more inclusive and stable financial ecosystem through prudent
digital technology integration.

本研究探讨数字银行和替代贷方对金融包容性的双重影响以及他们的商业模式所带来的监管挑战，通过对运营框架和技术基础设施的详细分析，确定了促进更广泛金融准入并缓解传统障碍的关键机制；此外还解决了与数据隐私、算法偏见、金融稳定和消费者保护有关的重要监管问题，通过定量金融数据分析与行业专家的定性见解相结合的混合方法研究，阐明了利用数字技术促进金融包容性的复杂性；研究结果强调了需要演进的监管框架，以将创新与全面风险管理相协调；本文最后提出了针对监管机构、金融机构和技术提供商的政策建议，旨在通过审慎的数字技术整合培育一个更具包容性和稳定性的金融生态系统。

加强金融包容性及监管挑战：数字银行和替代信贷在数字平台、机器学习和大型语言模型整合中的关键分析

Enhancing Financial Inclusion and Regulatory Challenges: A Critical  Analysis of Digital Banks and Alternative Lenders Through Digital Platforms,  Machine Learning, and Large Language Models Integration