The paper proposes a new approach to financial modeling, using Event Databases (EDBs) and a Model Server to address these challenges. EDBs can handle high- volume, high-velocity, and high-variety data, making them ideal for Artificial Intelligence (AI) and Machine learning (ML) applications. A Model Server can separate data from formulas, protect sensitive information, enable safe collaboration, and manage model approval and usage. The paper also highlights the importance of continuing to use Excel for financial modeling by leveraging its universal understanding and customization capabilities, while addressing its limitations through the proposed new approach.

Sponsored by:


  • Christopher L. Condron


  • Lisa Payne


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