Risk Analytics
Executive Summary This article explores the development of a scalable, high-performance risk analytics engine for financial institutions, leveraging Apache Beam and Google Cloud Dataflow. The project addressed the need for efficient, portable, and robust risk management solutions in a rapidly evolving regulatory and market environment, resulting in a modernized architecture that supports both batch and streaming analytics at scale. Business Context and Drivers Financial institutions face increasing regulatory scrutiny, market volatility, and the need for real-time risk assessment. Traditional risk engines, while functional, often struggle to scale and adapt to new requirements. The move to a cloud-native, distributed architecture was driven by the need for agility, cost efficiency, and the ability to process large volumes of data with low latency. ...