Executives in a Fortune 100 financial services firm had questions about the cost-efficiency of processes involved in managing a high volume of transactions across hundreds of internal systems. Process Intelligence enabled their analysts to turn around data-driven answers rapidly—and find where process improvements would yield significant ROI.
Challenge
Research analysts at a leading financial institution needed to provide data about the cost-efficiency of their high-volume transaction processes. To examine the processes completely, the analysts needed to access data from 40 different systems, ranging from customer interactions to back-office workflows.
The analysts wanted a process mining solution that would easily visualize all of this process data end to end, without requiring coding, so they could:
- Gain a truly end-to-end perspective of transaction processing, from customer request to fulfillment
- Determine how many transactions are processed straight through
- Identify processes where redesign and automation offer the best ROI
Solution
Process Intelligence aggregated event data from two million transactions daily across enterprise-wide systems into a live data stream. Analysts could finally follow a transaction’s execution progress from beginning to end, along a timeline.
Process Mining revealed transaction paths where distributions were significantly delayed by manual handling, providing an opportunity for $3.6M in savings through automation.
The solution also helped analysts find a specific type of transaction with higher delay and market exposure, resulting in $2.4 million in expenses that could be avoided.
Customer service analysts found key points of high friction in customer processes.
Value
- A live, end-to-end view of transactions from 2M daily events and 40 different systems on a timeline—without coding
- $6M in potential savings identified through process improvement and automation
- Sources of high friction early in customer service processes identified and alleviated
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Originally posted on 2024-12-18 in the IRPA AI Network — Intelligent Automation