How automation helped a top U.S. bank cut handling time in half and increase accuracy by 80%.

Customer: One of the top 10 banks in the U.S.
Problem

For years, the bank’s commercial loan booking team had failed to comply with SOX regulations. The loan booking process was highly manual, requiring analysts to key 80+ data fields into a booking system, which made it slow and prone to error, despite rigorous quality controls.

Solution

The bank implemented WorkFusion’s Smart Process Automation. Machine learning bots were trained to automatically extract key data fields from several types of unstructured loan documents. A visual audit trail makes the process transparent, enabling checkers to trace back how the bots interpreted the data.

Benefit

A digital workforce is born. Bots take on the bulk of work upfront by automatically extracting a majority of key data fields. The analyst's role shifts to focus more on the complex loans that couldn't be automated (i.e., exceptions) and performing quality assurance. This transformation enabled the bank to commit fewer errors while also reducing manual handling time per loan document.

Impact
80%
Increased accuracy of data entry
6WKS
WorkFusion SPA end-to-end implementation time
50%
Reduced manual handling times per load
How did we do it?
Find out more about the AI-driven RPA capabilities in WorkFusion’s Smart Process Automation and how we automate work that’s too complex for rules by turning high-volume data into smarter automation.
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