Business Problem

A leading financial services firm is experiencing significant inefficiencies in processing historic as well as current financial data stored in various PDF formats. These PDFs include a mix of editable and pictorial content with varying degrees of clarity. These PDFs included following data

• PDF Forms
• Text in pictorial Format

including historical documents and scanned images. The manual extraction process is labor-intensive and error-prone, affecting the firm’s operational efficiency and decision-making speed.

Challenges:

Inconsistent Data Formats: The data received in different structures for same category

Complexity of Data Extraction: Efficiently extracting and digitizing financial data from old company records stored in PDF and scanned image formats, with varying degrees of clarity.

Data Analytics: Converting extracted data into a structured format for financial analysis and reporting.

Scalability/Cost: Handling large volumes of data using scalable and reliable technology and also Cost Efficient.

Rite Solutions 

Following is the architecture

Implementation:

Data Extraction Engine:

• Developed an AI-powered OCR system to accurately extract text from PDFs, with varying clarity.
• Implemented Python scripts to automate the extraction process, reducing the need for manual intervention.historic 

Scalable Infrastructure:

• Deployed the solution on AWS using Amazon ECR for container orchestration, ensuring high availability and scalability.
• Utilized MongoDB for its scalability and flexibility in handling large datasets.

Benefits

Work Digitalization:

• Automated the extraction process, significantly reducing the need for manual data entry and validation.
• Enabled the firm to transition from paper-based processes to digital workflows, enhancing overall efficiency.

Time and Cost Savings:

• Reduced data extraction and processing time from several man-hours to just a few days.
• Lowered operational costs by minimizing manual labor and reducing errors associated with manual data handling.

Improved Data Accuracy and Availability:

• Enhanced the accuracy of extracted data using AI and OCR technologies as high as 80 % accuracy.
• Made historical financial data readily available for analysis, aiding in better decision-making and strategic planning.

Scalability and Future-Proofing:

• Implemented a scalable solution capable of handling increasing volumes of data as the business grows.
• Configurable functionality to linearly increase and integrate new companies to extract the company information

Conclusion:

By implementing this advanced PDF data extraction solution, the company has transformed its data handling processes, leading to significant improvements in efficiency, accuracy, and cost-effectiveness. This strategic move not only enhances their current operations but also prepares them for future growth and technological advancements.

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