ISDA DIGITIZATION
Reduce risk, increase compliance, and improve productivity
Digitize your ISDAs, and other capital market documents, and increase data capture productivity by 80% with pre-trained models.
Goldman Sachs straight-through processes up to 1.5K documents daily with Eigen
See how Goldman Sachs leverages Eigen to efficiently analyze their QFC portfolio (including the ISDA family of documents) of 50+ agreement types on an ongoing basis.
Get immediate ROI and straight-through process ISDAs with our pre-trained models
Whether it's to support regulatory reporting such as QFC and BRRD, risk management, general records keeping or improve data quality, Eigen's ISDA Digitization Pack includes +100 pre-built fields and enables you to:
- Automate the processing of information and insights from ISDA documents with +98% data accuracy
- Perform data remediation with human exception handling workflows based on your business needs
- Easily extract, validate and download the information you need from the ISDA family of documents
- Send the data to your downstream IT systems and databases via our REST API or integration partners
The Benefits of Eigen's ISDA Digitization Pack
Boost transparency on committed clauses and improve your ability to track and manage risk.
+90% OOTB accuracy. Benefit from superior accuracy with custom confidence targets and human exception handling workflows to further improve data quality.
+100 pre-built questions. Unlock immediate value with our pre-trained models. Easily add your own questions as required based on your business needs.
Identify enforceable terms. Leverage Eigen’s framework for parent/child mapping to identify relationships across ISDA Master, Schedule, CSA and amendments.
Enterprise-grade model risk management (MRM). Eigen's OOTB MRM framework allows for quick deployment and compliance with even the strictest G-SIB processes.
How Eigen extracts data from ISDA documents
Capture ISDA documents
Ingest documents from any source
Integrate Eigen with your email systems or document repositories to automatically detect and ingest new ISDA family documents as they arrive, or drop files straight into the user interface. Either way, you can easily and immediately extract over 100 commonly required terms from ISDA documents.
Integrate Eigen with your email systems or document repositories to automatically detect and ingest new ISDA family documents as they arrive, or drop files straight into the user interface. Either way, you can easily and immediately extract over 100 commonly required terms from ISDA documents.
Classify ISDA documents
Eigen can classify ISDA Master Agreements, CSAs and amendments
Using machine learning, Eigen automatically classifies documents into their respective document types (ISDA master, schedule, CSA and amendments) including identifying and separating sub-documents contained within a single file (also known as deblobbing) in order to extract the appropriate data elements from each document.
Using machine learning, Eigen automatically classifies documents into their respective document types (ISDA master, schedule, CSA and amendments) including identifying and separating sub-documents contained within a single file (also known as deblobbing) in order to extract the appropriate data elements from each document.
Data extraction
Extract data at scale, even if there is variation in the wording
Eigen understands the context around an answer, as well as the content of the answer itself, allowing it to extract the contextually correct instance of a particular term/phrase/text string from subsequent ISDA documents. By taking both into consideration, Eigen develops a conceptual understanding of the information and leverages that to extract similar information from documents it has not seen before, even if the same concept is worded differently.
The ISDA pre-trained models are specifically trained on the ISDA family of documents to ensure data accuracy and quality.
Eigen understands the context around an answer, as well as the content of the answer itself, allowing it to extract the contextually correct instance of a particular term/phrase/text string from subsequent ISDA documents. By taking both into consideration, Eigen develops a conceptual understanding of the information and leverages that to extract similar information from documents it has not seen before, even if the same concept is worded differently.
The ISDA pre-trained models are specifically trained on the ISDA family of documents to ensure data accuracy and quality.
Associate ISDA documents
With intuitive parent-child mapping
Eigen extracts all tables within a document in combination with enforceable terms across amendments and related documents to give you a consolidated picture of provisions from umbrella agreements.
Eigen extracts all tables within a document in combination with enforceable terms across amendments and related documents to give you a consolidated picture of provisions from umbrella agreements.
Data post-processing
Act on your ISDA data
Customer-defined normalization and extraction rules can be applied post-extraction to standardize, clean, cross-reference or to compare data, among other things.
Customer-defined normalization and extraction rules can be applied post-extraction to standardize, clean, cross-reference or to compare data, among other things.
ISDA data validation
Eigen flags high and low confidence answers
Eigen provides human-in-the-loop capabilities with the ability to review the original document and remediate the extracted data. Additionally:
- Rules can be applied to any given extraction to validate data accuracy
- Each extraction is flagged as high or low confidence based on configurable numerical thresholds
- Users can leverage a manual remediation workflow to correct machine predictions, add comments or flag extractions for further review.
All changes are captured in audit logs with UI and API export functionality, and changes can also be used to improve your model.
Eigen provides human-in-the-loop capabilities with the ability to review the original document and remediate the extracted data. Additionally:
- Rules can be applied to any given extraction to validate data accuracy
- Each extraction is flagged as high or low confidence based on configurable numerical thresholds
- Users can leverage a manual remediation workflow to correct machine predictions, add comments or flag extractions for further review.
All changes are captured in audit logs with UI and API export functionality, and changes can also be used to improve your model.
Data export and integrations
Seamlessly pass extracted data to other business systems
Data can be exported from Eigen in csv or xls format, or you can integrate Eigen directly with a variety of systems (like LoanIQ, SharePoint, Unqork, Xceptor, etc.) using Eigen's REST API.
Or, work with Eigen's Professional Services team to create an end-to-end workflow to extract and feed ISDA document data to your upstream and downstream business applications.
Data can be exported from Eigen in csv or xls format, or you can integrate Eigen directly with a variety of systems (like LoanIQ, SharePoint, Unqork, Xceptor, etc.) using Eigen's REST API.
Or, work with Eigen's Professional Services team to create an end-to-end workflow to extract and feed ISDA document data to your upstream and downstream business applications.
Data accuracy and model risk management
We take data accuracy and model risk management (MRM) seriously. As one of our core principles, we've developed our MRM framework to meet the needs of our enterprise clients. Eigen's three lines of defense ensure the data you receive and act upon is correct:
Eigen meets the highest security standards
Demo Eigen's ISDA Digitization Pack
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