Modern financial platforms operate in highly distributed, multi-cloud environments where system reliability, performance, and cost efficiency are critical. Traditional Site Reliability Engineering (SRE) practices are predominantly reactive and lack predictive intelligence. This paper introduces the Marella Reliability Model (MRM), an AI-driven observability and incident prediction framework designed to improve system uptime, reduce Mean Time to Resolution (MTTR), and optimize operational costs. The framework integrates machine learning, real-time telemetry, and FinOps principles to create a proactive reliability ecosystem. Empirical evaluation demonstrates measurable improvements in system resilience and cost efficiency, making the model applicable to fintech and large-scale cloud-native enterprises.