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Case Study
Financial Data Extraction
Excel Data Extraction to Map Balance Sheets for Piramal
“Transforming complex financial data into accurate, standardized, and analysis-ready records seemed a massive challenge, which we conquered through structured extraction and human validation.”
Piramal, a reputed company from India, looked for reliable support for extracting, mapping, and analyzing large volumes of balance sheet data. The project involved addressing missing information, resolving mapping errors, and reducing the effort associated with manual extraction. At Eminenture, we smartly combined Excel, Google, automation, standardization, and human expertise to extract and validate financial information efficiently. The structured approach helped create consistent and accurate datasets that supported reliable financial reporting, faster analysis, and improved productivity.
Challenges
The biggest question mark was how to handle a massive set of financial records after extraction. Furthermore, their mapping was also lengthy and full of inconsistencies. So, it was not a smooth journey to extract and clean financial records until we defined a process.
- Extracting large volumes of financial data efficiently.
- Addressing missing data across balance sheet records.
- Resolving data mapping errors.
- Reducing dependency on manual extraction.
- Maintaining consistency across financial datasets.
- Validating extracted information for accuracy.
- Completing the project within the required turnaround time.
Solutions Provided
As the struggle was to extract and clean gigantic data, we implemented a structured workflow for financial data extraction where automation and human-led quality checks made data scraping and mapping effortless. These solutions covered the following:
- Extracting balance sheet data from relevant sources.
- Mapping financial information into the required structure.
- Validating extracted records for accuracy.
- Identifying and correcting data inconsistencies.
- Standardizing financial data for consistent analysis.
- Automating repetitive extraction activities.
- Conducting human QA checks for final verification.
- Organizing data into analysis-ready Excel datasets.
- Delivering the processed data within the agreed TAT.
Process Used
Creating a systematic workflow for extracting, evaluating, validating, and then, standardizing financial records won half the battle for us. We designed each subset to integrate flawlessness while avoiding repetitive manual effort through these cleansing steps:
- Financial data source identification.
- Excel-based data extraction.
- Balance sheet data mapping.
- Missing data identification and validation.
- Data standardization.
- Automated processing of repetitive tasks.
- Human-led QA verification.
- Final data consistency checks.
- Timely delivery of analysis-ready datasets.
Result
The combination of automation, financial data consistency, and human-powered QA helped this brand to maintain a dependable database. The structured workflow reduced repetitive effort while improving the consistency and comparability of pricing information:
- Financial data successfully extracted and organized.
- 100% accuracy achieved across validated records.
- Balance sheet information accurately mapped.
- Missing data identified and addressed.
- Data mapping errors reduced through systematic validation.
- Standardized datasets supported consistent financial analysis.
- Human QA checks strengthened data reliability.
- Reduced manual extraction effort improved productivity.
- Faster access to structured data supported quicker analysis.
- On-time TAT ensured smooth business operations.
Presenting Performance with Facts
Figures to Measure the Accelerating Rate of Improvement
3.5
K+Data Researched
0
%Accuracy
0:1
KAI+Human
0.0
%Standardization
Success Stories
Eminenture-The globally acclaimed most trusted BPM company
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