Overview

The client, a prominent auditing and accounting firm based in the US, faced challenges extracting critical data from MCA-regulated filings, including corporate and regulatory documents from India’s Ministry of Corporate Affairs (MCA) portal. The complexity of unstructured document types and varying formats across jurisdictions made manual extraction inefficient and error-prone, creating a need for a streamlined solution to improve compliance, efficiency, and accuracy.

Challenges

The client faced several challenges in extracting data from MCA filings, which required advanced tools and innovative solutions to ensure operational efficiency and data accuracy.

• Document structure and layout variations posed significant challenges to standardizing data.
• Outsourcing to other vendors posed the risk of delivery delays, further complicating the process. 
• Managing and processing bulk filings required a scalable and robust solution.
• Manual methods were time-consuming, often resulting in errors, inconsistencies, and unreliable data, delaying critical reporting and decision-making.

The XDAS Approach

XDAS delivered a comprehensive workflow for automating data collection and processing MCA filings. By leveraging AI and advanced automation techniques, the system addressed challenges with unstructured and semi-structured documents, such as scanned images, PDFs, and structured forms. Key actions included extracting and validating metadata, ensuring standardized outputs, and integrating Human-in-the-Loop (HITL) validation for high accuracy. This end-to-end approach streamlined compliance-ready reporting and operational efficiency.

Automated data collection and processing

XDAS tackled the complexities of MCA filings using advanced OCR technology to extract data seamlessly from image-based documents. AI-powered parsing extracted critical financial statements, company information, and director details from structured and unstructured formats. Automated workflows facilitated bulk file uploads and efficient document classification, managing high volumes while ensuring speed and accuracy.

Metadata extraction and standardization

AI models were utilized to extract essential metadata, including CIN, company name, address, financial figures, and director details while resolving irregular layouts and inconsistent data structures through machine learning-based classification. The standardized outputs were stored in a centralized repository, providing real-time updates and smooth integration into the client’s systems for enhanced usability and consistency.

HITL validation

To maintain exceptional accuracy levels, XDAS integrated Human-in-the-Loop validation. Trained professionals reviewed flagged records to verify data accuracy and resolve inconsistencies. The final dataset underwent rigorous HITL quality checks before being delivered to the client’s repository, ensuring reliability for compliance and reporting purposes.

XDAS streamlined the entire workflow from data extraction to validation and reporting. By automating the whole process in-house, the client gained greater control over timelines, with a real-time tracking and monitoring dashboard, ensuring timely delivery of critical reports. This end-to-end automation minimized inconsistencies arising from vendor-reliant processes and gave the client complete visibility and control over every workflow step.

Results

• 99% accuracy in data extraction: Automated workflows ensured accurate data capture from varied layouts and formats of MCA filings.
• 50% faster processing: XDAS reduced processing time, enabling quicker decision-making and reporting.
• Seamless scalability: The platform seamlessly handled the growing volume of MCA filings, with an interface to track workflow progress, eliminating the need for outsourcing.
• Standardized and clean data: Ensured uniform, error-free, and analysis-ready data for better insights.
• Enhanced data quality: Addressed inconsistencies and errors using advanced machine-learning techniques.