Instant loan apps have become increasingly popular, providing users with quick and easy access to loans. However, their rapid growth has raised concerns about potential risks, such as predatory lending practices, high interest rates, and privacy issues. This study investigates user perceptions of these risks using machine learning techniques. It analyzes customer reviews of three popular Indian loan apps to identify user concerns. The findings show that while users value the convenience of these apps, they also express worries about high interest rates, privacy risks, and predatory lending practices. The study highlights the importance of user financial literacy, transparency and ethical behavior from app developers, and appropriate regulations to ensure consumer protection and fair lending practices. It suggests further research avenues such as user experience studies, regulatory frameworks, and algorithmic accountability. Overall, this study contributes to the ongoing discussion about responsible lending practices and consumer protection in the digital lending space.

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Risks in Instant Loan Apps: Analyzing User Perceptions Using Machine Learning Approach

  • A. Lekshmi,
  • J. Atul,
  • Adith J. Pillai,
  • M. Dhanya,
  • Sanju Kaladharan

摘要

Instant loan apps have become increasingly popular, providing users with quick and easy access to loans. However, their rapid growth has raised concerns about potential risks, such as predatory lending practices, high interest rates, and privacy issues. This study investigates user perceptions of these risks using machine learning techniques. It analyzes customer reviews of three popular Indian loan apps to identify user concerns. The findings show that while users value the convenience of these apps, they also express worries about high interest rates, privacy risks, and predatory lending practices. The study highlights the importance of user financial literacy, transparency and ethical behavior from app developers, and appropriate regulations to ensure consumer protection and fair lending practices. It suggests further research avenues such as user experience studies, regulatory frameworks, and algorithmic accountability. Overall, this study contributes to the ongoing discussion about responsible lending practices and consumer protection in the digital lending space.