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Capital Markets

Risk Analysis

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Watch free online webinars explaining use cases for Panopticon data visualization software in real-time risk monitoring and analysis

Monitor and Analyze Risk with Interactive Real-Time Dashboards

Clients use Panopticon data visualization software to monitor risk limit usage and to analyze risk data generated by an external risk engine. Our dashboards help users spot problems and opportunities in the data faster than is possible with any traditional reporting system.

This Market Risk Analysis Dashboard uses a Treemap, a Heat Matrix and Scatter Plots and provides extensive OLAP-enabled filtering capabilities.Common use cases include:

  • Market Risk
  • Credit and Counterparty Risk
  • Liquidity Risk
  • Fund Risk Management (in association with Performance & Attribution)

Chandresh Iyer, Citi's Global Head of Custody and Investment Administration Services, describes how Heatmaps and Treemaps function as part of the CitiDirect® PRISM system, an industry first performance and risk reporting middle-office application using Panopticon data visualization technology. Learn more about the CitiDirect PRISM system.

Full range of functionality for analyzing risk data

Many capital markets firms have contracts in place for trading & execution analysis and other applications for Panopticon.Whether you are looking at risk in real time, intraday, end of day, or on an historic basis, Panopticon supports key functions that make risk analysis much more effective and efficient, including the ability to:

  • Subscribe to full and parameterized streams from a CEP engine
  • Display and interact with hierarchies like book structure, product structure, counterparty structure, geographic, industrial, issuer rating, asset class, and so on
  • Dynamically change additive hierarchies and aggregate values based on end-user interaction
  • Drill and jump between data dimensions (for example, jump from book to positions to instrument to counterparty)
  • Perform risk aggregation and netting
  • Handle non-additive data sets like Value at Risk (VaR) where the aggregates must be retrieved from an external risk calculation engine
  • Time window and time period analysis to identify delta changes between time period
  • Visualize trends, clustering, correlations, and outliers

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