Major multi-asset London hedge fund uses AQMetrics for integrated data management and risk calculations

Reflecting your firm’s methodologies with integrated data management

A London-based hedge fund with a 20-year track record and global reach came to AQMetrics looking for a risk solution that would allow complex data management and would reflect their unique risk methodologies. 

Having used standard, packaged risk management solutions before, they said that many of the existing solutions are blackbox in nature and don’t have the flexibility to reflect the firm’s approach to risk analysis. Too often, manual amendments were made after the risk calculations are derived, resulting in a repetitive, iterative process.

The Solution

Ownership of automation and simplification of data management process, flexibility in risk calculations. 

Working with AQMetrics, this firm was able to take ownership of their data management process, giving them flexibility to exclude positions from their calculations – e.g. for hedging purposes.

In order to drive the self-service process in a controlled manner, a decision tree workflow in the AQMetrics platform walks the firm through the position and sub-asset class selection process, confirming the positions that will be included and those that require exclusion or non-standard treatment. At each step of the decision tree workflow, the steps are controlled, confirmed and audited, allowing a data management configuration to be replicated across all funds in the portfolio.

The Result

Data management and risk calculations that accurately reflect the firm’s methodologies and operations.

The result for the firm is that their data management and risk calculations now more accurately reflect the firm’s strategy, methodology and operations. The automated configuration is applied in real-time, removing the need for after-the-fact manual changes of risk calculations. This has allowed down-stream processes, such as regulatory and external reports (e.g open protocol) to be automatically populated with accurate and timely risk measures. 

Ultimately, the entire data and risk calculation process became more efficient for the firm, while they were also able to have better control and customisation of their data and risk methodologies.