Acadia announced the launch of IM Recalibration Analytics (IMRA), a tool that enables firms to assess the impact of new ISDA SIMM versions on their initial margin calculations. Users can assess new ISDA SIMM versions immediately and automate a range of tasks that are currently executed manually, such as viewing counterparty and netting set level exposure changes and daily trend analysis to track potential changes in IM differences.
The analytics tool also provides firms with greater visibility when comparing a variety of data points, such as aggregate exposure and counterparty- and agreement-level exposure.
Off-cycle recalibration was recently introduced to ensure that major market shocks that drive a significant change in risk can be factored into the ISDA SIMM model on a quarterly basis in addition to an annual basis. The introduction of potential quarterly off-cycle recalibrations makes having the capability to efficiently and accurately predict the impact of initial margin exposure calculation changes more important than ever.
Stuart Smith, co-head of Business Development at Acadia, said in a statement: “With the introduction of off-cycle recalibrations, firms need to remain agile and be able to quickly and efficiently assess new ISDA SIMM versions. We understand how crucial it is for firms to have the tools to hand that ensure they are best equipped to understand the impact of initial margin exposure. IMRA not only gives firms the tools to do so, it also provides them with a high level of visibility and accessibility. As a result, this enables firms to streamline processes, optimize resources, and forecast the impact of initial margin exposure with greater certainty, having a significant positive impact on a firm’s day-to-day processes.”
IMRA leverages existing services provided by Acadia for firms in-scope for Uncleared Margin Rules. By incorporating existing data from IM Exposure Manager and IM Threshold Monitor, IMRA gives users the added benefit of a complete, consistent view of their initial margin requirements without the need to upload new data.