Automating Statement Data Extraction
for NextWave Capital
NextWave Capital managed thousands of monthly bank and financial statements across multiple clients, each with unique layouts and reporting standards. Manual reconciliation and data entry not only consumed significant time but also introduced inconsistencies and errors. Extracting accurate financial data from scanned PDFs and tabular statements became a major challenge, slowing down reporting cycles and increasing compliance risks.
Disclaimer: This image is for demonstration purposes only and is not related to any real customer.
Reconciling over 5,000 monthly financial statements with varying formats and structures.
Human errors during manual reconciliation created reporting inaccuracies and compliance issues.
Extracting structured financial data from inconsistent sources such as scanned PDFs, spreadsheets, and tabular statements.
- Automated statement data extraction system
- AI-powered parsing of structured and unstructured formats
- Key field capture (Supplier Name, Opening Balance, Closing Balance Currency etc)
- Support for multi-format documents (scanned images, PDFs,)
Statement processing and reconciliation time reduced by 75%, accelerating monthly financial close cycles.
Error rates dropped by 98%, ensuring compliance and accuracy in financial reporting.
The automated solution scaled seamlessly as statement volume grew, without requiring additional staff.
By implementing automated statement data extraction, NextWave Capital transformed its reconciliation process, achieving faster reporting cycles, improved accuracy, and reduced compliance risks. This automation not only minimized the burden of manual work but also provided scalability, allowing the financial services provider to manage growing data volumes effortlessly while maintaining strict accuracy standards.
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