This paper analyzes the trade-off between credit risk and financial performance within the Canadian peer-to-peer lending market, focusing on the platforms Lending Loop and goPeer. Using a multistage empirical framework, including nonparametric diagnostics, Cox proportional hazards modeling and logistic regression, we examine how borrower characteristics and platform-assigned credit grades influence loan survival outcomes. Macroeconomic scenario analysis and Monte Carlo simulations are further employed to evaluate portfolio resilience under systemic shocks, including recessionary conditions and interest-rate fluctuations. The results indicate that platform credit grades provide economically meaningful risk segmentation, with higher-grade loans demonstrating relatively stable performance across borrowerlevel and macroeconomic perturbations, while lower-grade segments exhibit significantly greater sensitivity to borrower fundamentals and adverse economic conditions. These nonlinear responses suggest that borrowers closer to default thresholds amplify both microlevel and macroeconomic risk exposure. Overall, the findings highlight the importance of robust underwriting, adaptive risk management and diversification strategies as fintech lending platforms become increasingly integrated into broader financial and payment ecosystems.