Intelligent Automation
Large-Scale RPA Automation for a US Bank Processing $36.3B Across 603.7M Transactions.
Problem Statement
A US bank processing $36.3 billion across 603.7 million transactions annually, serving 88,000 small business merchants, relied on largely manual processes for mainframe data retrieval and transaction reconciliation.
At this scale, manual intervention increased operational effort, cost, risk, and compliance pressure, while limiting the bank’s ability to streamline reconciliation and improve data access.
Challenges
High operational costs
Reconciliation required manually capturing over 2,000 screenshots from mainframe systems.
Increased risk
Manual reconciliation, including manual data entry, introduced a high likelihood of human error.
SLA non-compliance
The reconciliation process took weeks to complete, regularly resulting in SLA breaches.
Dynamic workloads
Unpredictable transaction volumes made capacity planning difficult, straining manual processes further.
Solution
Stratacent designed and implemented an RPA-based automation solution to retrieve data directly from mainframe systems, eliminating the manual screenshot-driven process. The team built an automated, end-to-end, rules-based reconciliation engine to replace manual data entry and matching.
To support this at scale, Stratacent designed and built a central data platform for reconciliation, complete with standardized reporting, ensuring consistency and transparency across the process.
Value Delivered
Consistent SLA compliance
Automated processes now consistently meet SLA commitments, eliminating the weeks-long delays of the manual process.
Significant cost savings
Delivered approximately $2M in manual labor savings.
Higher productivity
Increased productivity by 200% through automation.
Improved accuracy
Reduced the error rate in the daily reconciliation process.
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