Challenges

1. Corporate action documents are critical in the financial industry, as they contain information on dividends, mergers, stock splits, and other events that impact investors and market participants.

2. However, the manual extraction of key data points from these documents was a slow and error-prone process. The client had a dedicated team of five employees managing corporate action data, but due to fluctuating document volumes and tight deadlines, operational inefficiencies were common.

3. The challenge was to develop an automated system that could extract and process large volumes of corporate action documents with minimal human intervention while ensuring high accuracy and compliance with financial regulations.

The Project

• To streamline data extraction, an AI-powered Semantic Extractor was deployed.
• This solution leveraged Agentic AI to analyze patterns within corporate action documents and Generative AI to structure extracted information into machine-readable formats.
• Key project components included:
  • Automated Document Processing: AI-based text and table recognition identified key data points.
  • Validation Rules: AI-driven checks ensured data quality and compliance with regulatory standards.
  • Seamless Database Integration: Extracted data was pushed into the client’s financial systems in real time.

Project Delivery

1.AI-powered Text Parsing:

• Semantic AI was trained on historical corporate action documents to recognize financial terms, event types, and key numerical values.
• AI-assisted classification automatically grouped documents based on event type.

2.Automated Data Integration:

• AI-driven validation ensured extracted data matched existing financial records.
• The system interfaced with internal databases and external market platforms for real-time updates.

3.Quality Assurance and Scalability:

• Machine learning models continuously improved accuracy based on feedback loops.
• The system was designed to scale and handle seasonal spikes in document volume.

Benefits

• 99.9% Time Savings: The time required for data extraction was reduced from hours to seconds.
• 98% Accuracy: AI-driven processing minimized errors.
• Operational Efficiency: The system freed financial analysts to focus on higher-value tasks.
• Scalability: AI allowed the system to handle increased document volumes effortlessly.

By leveraging AI, the client dramatically improved corporate action data processing efficiency, achieving significant cost and time savings while enhancing compliance and accuracy.

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