Banking — Named Entity Recognition for Regulatory Documentation

Overview

The primary purpose of this DAG is to extract named entities from regulatory documents using advanced natural language processing techniques. It ingests data from multiple sources, including PDF files and Word documents, which contain essential regulatory information. The ingestion pipeline begins with the extraction of text from these documents, followed by the application of named entity recognition algorithms to identify relevant entities such as organizations, dates, and monetary values. To

The primary purpose of this DAG is to extract named entities from regulatory documents using advanced natural language processing techniques. It ingests data from multiple sources, including PDF files and Word documents, which contain essential regulatory information. The ingestion pipeline begins with the extraction of text from these documents, followed by the application of named entity recognition algorithms to identify relevant entities such as organizations, dates, and monetary values. To ensure the accuracy of the extracted entities, a series of quality control checks are implemented, which involve validation against predefined criteria and potential human review. The validated entities are then stored in a centralized data warehouse, facilitating easy access and traceability for compliance purposes. In the event of a failure during processing, a robust recovery mechanism is in place to automatically restart the process, minimizing downtime and ensuring operational continuity. Monitoring key performance indicators, such as extraction accuracy and processing time, allows stakeholders to assess the effectiveness of the DAG. The business value of this DAG lies in its ability to streamline regulatory documentation processes, reduce manual effort, and enhance compliance with regulatory standards.

Part of the Enterprise Search solution for the Banking industry.

Use cases

• Enhances compliance with regulatory requirements
• Reduces manual data extraction efforts significantly
• Improves data accessibility for stakeholders
• Increases accuracy of regulatory documentation
• Facilitates faster decision-making processes