Eigen's NLP platform enables you to efficiently analyze your back book, identify what counterparties have historically agreed to and focus your negotiations on a shortlist of terms.
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Users upload a handful of documents and label the relevant data fields for extraction. Eigen uses this information to build a machine learning model.
The model then analyzes all new documents to retrieve the correct data points. The extracted data is exported or sent to other systems via APIs.
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Eigen enables clients to focus their time on making faster, more informed decisions, instead of analyzing pages of documents.
Below are just a few of the use cases Eigen can help your business tackle.
Quickly identify key facts about CLO tranches that enable you to build risk and return profiles without reading 400+ pages yourself.
Systematically verify that assets meet the portfolio-level criteria to qualify for Solvency II with minimal expert involvement.
Automatically identify governing law, cross default rights, and restrictions on the transfer of credit to ensure compliance.
Identify linked instruments and their fall-back and transition processes across a myriad of diverse contracts to mitigate your prudential risks.
Reconcile data of back book across multiple systems and create a single source of truth for the entire loan life-cycle.
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