A case on how automation handled export bill documentation and compliance, from PDF merging to final bank emails.
The Client
The client is a major player in the retail and gifting sector, focused on delivering handcrafted products that celebrate rich artisanal heritage. Founded with a passion for Indian handicrafts and the art of gifting, they work closely with skilled artisans and self-help groups to bring authentic, high-quality gifts to customers. Their extensive collection spans unique premium, utility, return, and corporate gifts, with options for personalization. With a presence across several cities and global delivery to 190+ countries, they have built a trusted reputation for design excellence and authenticity.
Challenges Faced by the Client
When a company ships its products to an overseas (international) customer, the payment for that shipment must be “regularized” by the bank, meaning the bank confirms to its home country’s regulatory body that the payment matches the shipment details. This is called Export Bill Regularization, a mandatory step for customs clearance.
However, the bank can only do this after the company provides the right documents and information for each export, including:
- HAWB: House Airway Bill (shipment tracking document)
- IRM: Inward Remittance Message (payment reference generated by the bank)
- EDI: Electronic Data Interchange (digital shipping data from Customs)
- Commercial invoice copies and other shipping information.
The company’s finance and export teams prepare and send these details to the bank. For our client, this process had some clear challenges:
- Time-consuming data collection: Details had to be gathered from multiple sources (bank portals, customs systems, internal records) before they could be compiled into one package for the bank.
- Manual cross-checking: Every payment had to be matched with the correct shipment and invoice, which was prone to errors when done manually. If anything is missing or unmatched, the bank sends it back for correction, delaying the process and potentially leading to non-compliance, risking the company’s credibility.
- Difficulty tracking pending cases: There was no system for knowing which export bills had already been submitted to the bank, which were pending, or which had been sent back for corrections.
Solutions
The client’s export bill regularization process had multiple steps, each requiring different documents and data entries before payments could be received from the bank. Since the bank will only release payment after these documents are verified and approved, every step must be accurate and prompt.
Upon consulting with the client and understanding their situation, we built a Power Automate workflow that handled all these steps from start to finish, ensuring nothing was missed and all details were accurate. Here is how our solution works:
- Collecting and Preparing Documents Automatically: The process starts with the shipping bills (PDFs) for each order placed. Automation merges these PDFs into a single file to avoid back-and-forth manual downloading and information gathering.
- Information Extraction to Fill EDI Sheet: Using Regex (a search-and-match method that helps identify and extract specific data points from documents), the required details for the EDI Sheet are extracted from the merged shipping bills. The bot then fills the EDI Sheet using the gathered information.
- Filling and Submitting the IRM Sheet: The automation then fills the IRM Sheet using data from the EDI Sheet, shipping bill, and invoices. This is mailed to the bank automatically once filled. Upon validation, the bank issues an IRM Number.
- Using the IRM Number for Final Submission: Once the IRM Number is received, the automation adds it to the EDI Sheet. Upon final submission, the bank then proceeds to verify the submitted document, and will disclose the cleared bills.
Solutions Benefits
The automation brought several clear advantages to the export bill regularization process:
- Faster Payment Processing: By automatically preparing and submitting the required documents to the bank, payments are now initiated much sooner, compared to manual handling.
- No More Repetitive Manual Work: Steps like filling the IRM sheet, downloading it, extracting data from shipping and delivery bills, and emailing the bank now happen without human effort, freeing the team’s time for other important work.
- Error-Free Data Entry: Using Regex-based data extraction ensures that figures, dates, and reference numbers from multiple documents are accurate, removing the risk of typos or mismatched details.
- Clear and Organized Records: All files (combined PDFs, IRM sheets, and supporting documents) are automatically stored, sorted as individual folders with appropriate file names, for audit trail and later compliance checks.
- Consistent Communication with the Bank: The system sends the correct documents to the bank at the right stage, every time, ensuring no missed steps or delays in approval.
Conclusion
With the new Power Automate solution, the client’s export bill regularization process moved from being slow and manual to a smooth, end-to-end automated workflow. Every key step (from combining documents, extracting details, and filling sheets to sending them to the bank) is now handled automatically, with zero missed actions. The client is highly satisfied, as the process now takes a fraction of the time, is error-free, and keeps a clear record for future reference. UB Technology Innovations, Inc. continues to deliver intelligent automation solutions that make complex processes easy and reliable for large retail enterprises.
About Us
UB Technology Innovations, Inc. (UBTI) is a leading global technology solution provider with over 3 decades of experience across all industries, specializing in Capital Markets, Logistics, and Healthcare. We are the preferred Microsoft Solutions Partner backed by a world-class team of Microsoft Certified experts with rich experience in Azure Cloud Platform and Data Analytics.
Winner of the prestigious Azure
Synapse Hackathon 2021 award
One of the Top 10 winners of the
Microsoft’s Azure AI & ML Workathon