Case Studies Fortune 50 Bank Achieves Significant Performance Gains with Snorkel Flow for News Analytics
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Fortune 50 Bank Achieves Significant Performance Gains with Snorkel Flow for News Analytics

Analytics & Modeling - Machine Learning
Analytics & Modeling - Predictive Analytics
Finance & Insurance
Business Operation
Software Design & Engineering Services
The bank needed an accurate way to tag companies in unstructured news text, link them to identifiers (e.g., stock tickers), and classify mentions by sentiment and other aspects. The existing solutions, including a black box vendor system and internal heuristic approaches, were not meeting the performance requirements. The bank required a more efficient and accurate method to handle the vast amount of unstructured data feeds and derive meaningful insights from them.
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The customer is a Fortune 50 bank, one of the largest and most influential financial institutions in the world. With a vast array of services ranging from retail banking to investment banking, the bank operates on a global scale, serving millions of customers. The bank is known for its innovation in financial services and its commitment to leveraging cutting-edge technology to enhance its operations. Given its size and scope, the bank deals with an enormous amount of data daily, making efficient data processing and analysis crucial for maintaining its competitive edge.
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The bank implemented Snorkel Flow to develop an AI-powered news analytics application. This application was designed to monitor press coverage of target companies in unstructured data feeds. Snorkel Flow enabled the bank to accurately tag companies in news text, link them to relevant identifiers such as stock tickers, and classify mentions by sentiment and other aspects. The AI-driven approach provided a significant improvement over the legacy systems, allowing for more precise and faster data processing. The implementation of Snorkel Flow streamlined the bank's ability to analyze news data, providing more accurate and timely insights into market trends and company performance.
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The bank achieved a 25+ point performance gain over the legacy vendor system and internal heuristic approaches.
The news analytics application developed with Snorkel Flow reached a +90 F1 score, indicating high accuracy in tagging and classification tasks.
The implementation was 45 times faster compared to the traditional hand-labeling process, significantly reducing the time required for data processing.
+90 F1 score for news analytics application
45x faster compared to hand-labeling
+25% performance gain over black box vendor system
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