This study investigates the effectiveness of alternative credit risk management mechanisms within Peer-to-Peer (P2P) lending platforms, focusing on the impact of automated credit scoring, platform reputation and security, and credit risk monitoring on credit risk mitigation. Grounded in the Technology Acceptance Model (TAM), the research examines how stakeholder perceptions and digital tools influence lending outcomes in the FinTech landscape. Using a structured survey of 497 respondents, data were analyzed through SPSS using reliability testing, correlation, and regression analysis. Results show that platform reputation and security have the strongest positive effect, followed by credit risk monitoring. Automated credit scoring, while significant, showed a negative effect, indicating concerns about over-reliance on algorithms. The findings underscore the importance of trust, transparency, and monitoring in digital credit systems, offering practical insights for platform designers, regulators, and financial institutions seeking to improve credit governance through technology.