Risk Management

Barra®One
A multi-asset class, multi-currency risk and performance analytics platform that enables investors to use its risk forecasting model, correlated stress test engine and performance analytics together in an integrated fashion. Read more

RiskMetrics® RiskManager
A multi-asset class, scalable SaaS framework for enterprise-wide risk management.  RiskManager’s powerful analytical capabilities enable clients to quickly set up custom reports, run ad hoc analyses, perform exception management, design stress test scenarios and conduct what-if analysis. Read more

RiskMetrics® CreditManager
Sophisticated tools for consolidating and comparing risk and opportunities across an entire credit business -- including bonds, credit derivatives and traditional retail exposures. Read more

RiskMetrics® HedgePlatform
A service that helps investors to better manage their hedge fund investments using analytics calculated on the position-level holdings of each fund. Read more. Case Study: Using MSCI HedgePlatform for holdings-based risk management - A case study for the State of Wisconsin Investment Board. 

RiskMetrics® WealthBench
A web-based platform that helps wealth managers assess portfolio risk, construct asset allocation policy and create comprehensive client proposals. Read more

Stress testing is used to identify potential losses due to event-related risks that may not be captured by standard Value at Risk (VaR) analysis.

In addition to helping clients address regulatory requirements for stress testing, our extensive library of historical and predictive stress tests helps clients with business planning by giving them a clear view of their structural and tail risks. Learn more about multi-period stress testing which allows investors to understand the impact of scenarios that can occur over multiple market cycles.

Our stress tests can be fully customized by adding shock parameters, correlation assumptions and other measures. For more information please read here.

Our well-respected tools for statistical analysis provide clients with a broad range of risk calculations on a daily and weekly basis.

One of our best-known statistical models is Value at Risk (VaR), which calculates the largest possible loss that could be incurred in a portfolio at a specific probability level over a given period of time.

In December 2014, we proposed three methods for back-testing Expected Shortfall that are shown to be more powerful than the Basel VaR test. These tests generally require storing more information, but introduce no conceptual limitations or computational difficulties.