Top 3 US bank Leverages AI and NLP to streamline financial document processing
公司规模
1,000+
地区
- America
国家
- United States
产品
- Snorkel Flow
技术栈
- Natural Language Processing (NLP)
- Programmatic Labeling
- Weak Supervision
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Digital Expertise
- Productivity Improvements
技术
- 分析与建模 - 机器学习
- 分析与建模 - 自然语言处理 (NLP)
- 应用基础设施与中间件 - 数据交换与集成
适用行业
- 金融与保险
适用功能
- 商业运营
- 质量保证
服务
- 软件设计与工程服务
- 系统集成
- 培训
关于客户
The customer is a top 3 US bank, which is a major financial institution with a large team of financial analysts. These analysts are responsible for reviewing financial documents, such as 10-Ks, to find specific information like interest rate swaps. The bank is focused on improving operational efficiency and leveraging advanced technologies to enhance their services. With a significant number of employees and a vast amount of financial data to process, the bank is looking for innovative solutions to reduce manual workload and improve accuracy in data extraction.
挑战
Analysts at this top 3 US bank spend hundreds of hours a year manually reviewing financial documents to find information on interest rate swaps. This manual process is time-consuming and takes away from their ability to assist customers proactively. The team recognized the potential of using AI and NLP to streamline 10-K processing but lacked the training data required to train a model that could automatically identify and extract interest rate swaps from 10-Ks accurately across multiple formats.
解决方案
The bank leveraged programmatic labeling and weak supervision to encode analyst expertise as labeling functions (LFs). This approach allowed them to train a custom NLP model that could automatically identify and extract interest rate swaps from 10-Ks. The model achieved an F1 score of 83 in just a few weeks. By using Snorkel Flow, the team was able to generate 70,000 labels per minute programmatically, significantly speeding up the training process. This solution not only reduced the time spent on manual document review but also improved the accuracy and consistency of the extracted data.
运营影响
数量效益
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