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Case Study

Automating Loan Document Management and Tracking for a Financial Services Organization

Client Overview

A prominent financial services provider managing high volumes of loan documentation needed a reliable solution to reduce manual workload, improve document traceability, and maintain compliance. Their operations involved working with multiple systems—EDMS (web-based) and Lakewood (Windows-based)—to manage, update, and track loan-related documents and status reports.

Challenges

  1. Manual Document Handling – – Processing documents for each loan number involved searching, compiling, and uploading multiple files manually from shared folders, which was both time-consuming and error-prone.
  2. Multi-System Coordination – The use of both EDMS and Lakewood systems added complexity and increased the chance of misalignment or duplication.
  3. Lack of Standardized Tracking – – Tracking loan conditions and updates required manual Excel-based processes, delaying turnaround and reducing audit readiness.
  4. Repetitive and Labor-Intensive Workflow – Employees had to repetitively input data and upload files for every single loan, reducing efficiency and increasing costs.

Solutions: Integrated RPA with IQ Bot and System-Level Automation

To overcome these challenges, RESOLVENT deployed an advanced automation solution combining RPA and cognitive capture (IQ Bot) to manage the end-to-end loan documentation and tracking process.

Automation Workflow Highlights:

  1. Cognitive Document Extraction (IQ Bot) – The bot used IQ Bot to intelligently extract data from various loan documents stored in shared folders, organizing them by loan number.
  2. Excel Generation & Uploading – For each loan, the bot generated an Excel sheet summarizing key details, then uploaded it into the EDMS application under the corresponding loan record.
  3. Document Upload Automation – The bot picked all loan-related documents from shared folders and uploaded them into the EDMS system based on loan numbers, reducing manual file management.
  4. Lakewood System Updates – The bot used the Excel sheet to update required fields and track items in the Lakewood system, ensuring real-time updates for each loan.
  5. Condition Site Creation & Upload – After completing the tracking, the bot generated a condition report (site) and uploaded it back to EDMS, creating a centralized loan information repository.

Results & Impact

  • 75% Reduction in Manual Processing Time – Automation cut processing time from 40+ minutes per loan to under 10 minutes, accelerating the entire workflow.
  • Improved Accuracy & Compliance - Standardized data extraction and structured updates reduced manual errors and improved regulatory readiness.
  • Seamless Integration Across Platforms - Automated workflows synchronized data and documents between EDMS and Lakewood, enhancing system consistency.
  • Efficient Document Handling – Automated document retrieval, classification, and uploads improved file traceability and organization.
  • 30–40% Operational Cost Savings – Reduced reliance on manual labor and minimized rework contributed to substantial cost efficiency.

Conclusion

By implementing an IQ Bot-powered RPA solution, the financial institution streamlined its loan documentation process, enhanced tracking accuracy, and achieved measurable gains in productivity and compliance. This automation has laid the groundwork for scaling operations while maintaining exceptional service standards.