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Automated Margin Call Management


Regulations such as EMIR in Europe, Dodd-Frank in the US and others have increased required margin exchanges to ensure that there is sufficient collateral, if needed. But high-quality collateral demands are difficult to meet with the current technology and operations available for collateral management. In fact, 15% of collateral is currently left idle, costing ~$4.5 Bn/year.

The current practice in the collateralized OTC derivatives market is to exchange margin call notices, and confirmations of collateral settlement without the use of any centrally-defined standard message format. These notices are delivered via various media, predominantly email. Therefore, firms are looking for ways to automate their margin calls to optimize their collateral management.

Synechron’s Robotic Process Automation Accelerator for Margin Call Management uses machine learning for margin call email automation. The solution uses Natural Language Processing (NLP) technologies and automation techniques to process email communications related to OTC Derivatives margin calls and automatically transmit that data into collateral management systems as an authoritative data source for human verification; thereby, speeding up collateral management, increasing accuracy and positively impacting collateral costs.

Features: Automated Processing of Margin Call Emails

  • Email Parsing: The system will have the ability to parse emails and look for margin-related information either in the body of the email or in the email attachments (such as word, pdf or excel). Since there is no pre-defined template, the format of the email exchange can be different across multiple counterparties.
  • Ascertain Margin information: Using accurate NLP techniques, the Robotic Process Automation engine will be able to distinguish a margin response email (which could either be partial or full agreement or dispute) from an anticipated margin call from the other counterparty. Some of the relevant attributes that will be identified include the margin call value, MTM value, Currency, Account Number, etc.
  • Collateral Management Integration: Once the Robotic Process Automation engine identifies the relevant margin attributes, the system will have the capability to trigger a call to the collateral management system and pass on the required information. To begin with this can be a manual process (requiring human intervention). However, once the Robotic Process Automation engine achieves the required rate of success, this process can be automated further minimizing operational overhead.

To learn more about our Artificial Intelligence solutions for Robotic Process Automation and the work we’re doing email us at