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Case Study

Automating Loan-Based Document Handling and Condition Reporting

Client Overview

A leading financial services provider specializing in loan processing and servicing needed to streamline how loan documents and conditions were managed across two critical systems—Lakewood (Windows-based) and EDMS (web-based). The manual process of downloading, extracting, and organizing data based on loan type created operational bottlenecks and reduced turnaround efficiency.

Challenges

  1. Loan-Type Based Document Segregation – Employees manually accessed the EDMS application to retrieve documents tied to specific loan types, which was time-consuming and error-prone.
  2. Field Extraction & Condition Reporting – Extracting and organizing key data points in the Lakewood system based on loan type required repetitive effort.
  3. Manual Uploads to EDMS – After generating the condition reports in Excel format, uploading them back into EDMS was an additional burden on the operations team.
  4. Lack of Integration – No direct linkage existed between document extraction, field processing, and reporting, creating workflow silos.

Solutions: End-to-End Loan Type Automation via RPA

The RESOLVENT delivered a tailored RPA solution to fully automate the loan-type-driven process between EDMS and Lakewood, from document retrieval to condition reporting and uploads.

Key Automation Capabilities:

  1. Automated Document Download (EDMS) – The bot intelligently accessed the EDMS application to retrieve documents based on predefined loan types, eliminating manual filtering.
  2. Smart Field Extraction (Lakewood) – The bot launched Lakewood and automatically extracted relevant loan fields tied to each loan type, ensuring accuracy and completeness.
  3. Condition Report Generation – Based on the extracted data, the bot generated a loan-specific condition Excel sheet, following business rules for formatting and structure.
  4. Document Upload to EDMS – The condition site Excel was then automatically uploaded into EDMS, neatly aligned under the appropriate loan number and record.

Results & Impact

  • 60% Faster Document Handling – Reduced time spent downloading, processing, and uploading loan documents manually.
  • Consistent & Accurate Data Capture Eliminated manual entry errors, improving data integrity across loan records.
  • Improved Loan Condition Reporting Automated generation of condition sites resulted in standardized, audit-ready documentation.
  • Operational Efficiency Boost – The streamlined process lowered administrative effort and freed up the team for exception handling.
  • Seamless Workflow Integration – Bridged the gap between Lakewood and EDMS, creating a cohesive loan processing flow.

Conclusion

By leveraging RPA to automate document retrieval, field extraction, and report generation, the client achieved significant process improvement across its loan management operations. The automation helped increase speed, accuracy, and compliance—positioning the company for scalable growth and better client service.