Today, we’re releasing a new solution for financial graph machine learning (ML) in Amazon SageMaker JumpStart. JumpStart helps you quickly get started with ML and provides a set of solutions for the most common use cases that can be trained and deployed with just a few clicks.
The new JumpStart solution (Graph-Based Credit Scoring) demonstrates how to construct a corporate network from SEC filings (long-form text data), combine this with financial ratios (tabular data), and use graph neural networks (GNNs) to build credit rating prediction models. In this post, we explain how you can use this fully customizable solution for credit scoring, so you can accelerate your graph ML journey. Graph ML is becoming a fruitful area for financial ML because it enables the use of network data in conjunction with traditional tabular datasets. For more information, see Amazon at WSDM: The future of graph neural networks.
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