Proactive Risk Monitoring and Alerting System for Investment Portfolios Using AI Agents in Cloud

The dynamic complexity and volatility of modern financial markets have rendered traditional, reactive risk modeling insufficient for managing investment portfolio risks in real time. This paper addresses the limitations of conventional approaches by proposing a proactive risk monitoring and alerting system that leverages AI agents in cloud environments to autonomously observe, analyze, and respond to market positions, systemic stress factors, and timely news events. The architecture incorporates real-time data ingestion pipelines, natural language processing for sentiment analysis, and recommendation engines for automated hedging strategies, orchestrated over cloud-native infrastructures to ensure scalability and resilience. The proposed system not only promises to reduce latency and enhance adaptability but also implements multi-agent orchestration patterns that facilitate robust, specialized, and collaborative analytics. Evaluation metrics are designed to measure system accuracy, latency, scalability, and resilience to security threats and model drift.