Perform root-cause analysis on margin changes over time and conduct attribution studies.

• Once margin movements have been identified, drill down to understand their underlying causes.
• Thoroughly investigate the key drivers behind the margin changes through attribution analysis – crucial for deciphering shifts within complex risk models like SIMM. Map changes across granular categories such as product class, risk type, qualifier (e.g., currency, issuer), trade status, SIMM version for IM and sensitivity type.
• Quickly identify high-impact trades that have the greatest influence on margin changes, enabling a more focused analysis and attention where it’s needed most.
• Understanding the root causes allows you to more accurately gauge risk exposures and implement targeted actions to address potential issues.

Assess the impact of new transactions or market moves with pre-deal checks & market data stress testing 

• Assess the impact of new transactions on overall margin requirements before executing with our pre-deal check.
• Understand how potential volatility or market shifts could influence margin levels by stress testing portfolio resilience using hypothetical scenarios and historical stress events.
• Ensures that both trading and risk teams have a solid foundation for proactive decision-making regarding liquidity usage and funding.

Verify IM sufficiency for historical P&L and gain insights into evolving margin requirements

• Validate the effectiveness of the SIMM IM model by ensuring that the initial margin collected is sufficient to cover potential losses over a specified period with backtesting.
• Assess the robustness of the risk control framework and support compliance with regulatory requirements.
• Forecast and get insights into how margin requirements may evolve over time.