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Global financial services leader extracts financial information from PDFs with 99% accuracy
技术
- 分析与建模 - 数据挖掘
- 分析与建模 - 机器学习
适用行业
- 金融与保险
适用功能
- 商业运营
服务
- 软件设计与工程服务
挑战
The bank needed to extract structured financial data from balance sheets and income statements (hOCR PDF) from private company financials. This task was challenging due to the unstructured nature of the data and the need for high accuracy in financial reporting. Traditional methods, such as manual data entry or rules-based systems, were time-consuming and prone to errors. The bank required a solution that could automate the extraction process, improve accuracy, and handle the variability in document formats and data presentation.
关于客户
The customer is a global financial services leader, known for its extensive range of financial products and services. This organization operates on a large scale, serving millions of clients worldwide, including individuals, businesses, and institutions. The company is committed to leveraging advanced technologies to enhance its operations and deliver superior services to its clients. With a focus on innovation, the financial services leader continuously seeks to improve its processes, particularly in areas that involve large volumes of data and require high precision, such as financial data extraction and analysis.
解决方案
The bank implemented Snorkel Flow to develop an AI-powered financial spreading application. This application was designed to parse both textual and spatial/visual data features from financial documents. By leveraging machine learning and data mining techniques, the application could accurately extract structured financial data from unstructured documents. The use of Snorkel Flow allowed the bank to automate the data extraction process, significantly reducing the time and effort required for manual data entry. The AI-powered solution also provided greater generalizability, enabling the bank to handle a wider variety of document formats and data presentations with high accuracy.
运营影响
数量效益
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