We made a visible and
measurable impact to our
client's business
Reduction in Reconciliation Processing Time
Annual Operational Hours Saved
Return on Investment Achieved
About the Client
A leading financial institution managing large-scale financial operations and enterprise reconciliation workflows across critical banking environments. As transaction volumes and operational complexity increased, the organization required a faster, more accurate, and scalable reconciliation framework capable of improving operational efficiency and reducing manual dependency.
The bank sought to modernize reconciliation operations through intelligent automation to accelerate financial processing, improve data accuracy, and streamline enterprise finance workflows.
The Problem
The organization’s reconciliation process relied heavily on manual operations, creating significant inefficiencies and operational delays across financial workflows.
Key challenges included:
- Manual reconciliation cycles consuming more than 400 operational hours
- High dependency on repetitive manual processes and validations
- Frequent reconciliation errors impacting operational accuracy
- Delayed financial reporting and operational decision-making
- Limited scalability to support increasing transaction volumes
- Operational bottlenecks affecting finance team productivity
- Previous optimization initiatives failed to deliver sustainable automation capabilities
The organization required an intelligent automation solution capable of modernizing reconciliation operations while improving speed, consistency, and operational scalability.
Our Approach
Lauren Group implemented a Robotic Process Automation (RPA)-driven reconciliation framework designed to automate end-to-end financial reconciliation workflows and improve operational efficiency across banking operations.
The solution enabled:
- Automated reconciliation between bank statements and Oracle EBS systems
- Reduced manual intervention across financial operations
- Faster reconciliation processing and reporting cycles
- Improved financial accuracy and workflow consistency
- Seamless integration into existing enterprise finance environments
- Scalable automation capabilities designed for growing transaction volumes
Tech Stacks Used
RPA Platform
Oracle EBS
The Result
- Reduced reconciliation processing time by 95%
- Accelerated reconciliation cycles from 400 hours to 20 hours
- Saved 16,775 operational hours annually
- Achieved an ROI of ₹2.17 crore through automation-driven efficiency
- Improved financial accuracy and reconciliation consistency
- Reduced manual workload across enterprise finance operations
- Established a scalable and future-ready reconciliation automation framework