New products, data sources, and regulations are increasing risk analysis complexity for financial institutions. Today’s environment demands risk management solutions that provide greater agility and operational efficiency, using more powerful and cost-effective computing solutions to implement increasingly complex risk models, integrate data at scale, and satisfy increasing demands for real-time responsiveness.
The risk calculation process starts with ingesting data from different sources, extracting, transforming, and loading (ETL) it into a distributed cloud for risk calculation. Some data and events are processed in real time, using techniques such as complex event processing and streaming analytics to synthesize external events into business-relevant market events used to trigger new risk calculation processes. The calculations evaluate the risk profile of assets and portfolios, taking into consideration various market scenarios using risk models and algorithms, typically as largely parallel computations. This can happen in a single step, or as a complex sequence of risk calculations that are coordinated via automated business processes. Risk calculations can be scheduled or performed in real time.
