Case Study · Payment Operations Automation

Returned Payments Process Automation & Capacity Recovery

Redesigning high-volume returned payment workflows into a more scalable, automation-enabled operating model that eliminated 160+ manual hours per week and recovered approximately four FTEs of operational capacity.

160+
Manual Hours Eliminated Weekly

The redesigned process reduced repetitive manual intervention, improved processing speed, and created a scalable framework for handling returned payment activity without proportional staffing increases.

  • Recovered approximately four FTEs of operational capacity
  • Reduced backlog risk across high-volume payment workflows
  • Improved consistency and accuracy across payment handling
  • Freed team capacity for higher-value exception resolution and analysis

Context

At Charter Communications, returned payment operations supported a multi-million-customer environment involving payment exceptions, reversals, and downstream account impacts across billing and collections workflows.

The function operated at high volume and required timely, accurate processing. However, much of the work relied on manual review, repetitive intervention, and fragmented handling across teams.

As transaction volume increased, the process became harder to scale efficiently and created growing pressure on operational capacity.

The Operational Breakdown

The issue was not simply that the team had too much work. The deeper problem was that highly repeatable operational activities were still being handled through labor-intensive manual processes.

  • Returned payment processing required extensive hands-on review and intervention
  • Workflows were fragmented across teams with inconsistent execution methods
  • High transaction volumes created backlog risk and slowed processing timelines
  • Manual effort introduced variability and increased the risk of inconsistent outcomes
  • Teams were heavily dependent on repetitive tasks, limiting capacity for higher-value work
The operation needed a more scalable model that separated repeatable rule-based work from true exception handling.

Approach

The work began with a detailed review of end-to-end returned payment workflows to identify bottlenecks, redundancies, manual dependencies, and opportunities for automation.

Activities were segmented into rule-based tasks that could be automated and decision-based activities that still required human review, judgment, or exception handling.

  • Analyzed end-to-end workflows to identify bottlenecks and redundant steps
  • Separated rule-based activities from decision-based exception handling
  • Redesigned workflows to eliminate unnecessary manual steps
  • Partnered with IT and banking partners to support automation implementation
  • Standardized workflows and structured procedures for consistency
  • Established controls to maintain accuracy and proper exception handling

Solution

The redesigned operating model embedded rules and processing logic into automated workflows, reducing the need for manual review across high-volume transaction activity.

Instead of scaling the process through additional manual effort, the workflow was rebuilt to handle repeatable processing through system-driven execution while preserving clear controls for exceptions and escalations.

  • Automated high-volume returned payment workflows with minimal manual intervention
  • Embedded rules and logic into system-driven processing
  • Standardized exception handling and escalation paths
  • Improved consistency across payment handling workflows
  • Created a scalable processing model without proportional staffing increases

Results

The automation and workflow redesign significantly reduced manual effort while improving speed, consistency, and scalability across returned payment operations.

  • Eliminated 160+ manual hours per week, equal to approximately four FTEs of capacity
  • Increased processing speed and reduced backlog risk
  • Improved consistency and accuracy across payment handling
  • Freed team capacity for higher-value exception resolution and analysis
  • Established a scalable framework for ongoing automation and improvement

Key Capabilities Demonstrated

Process automation and workflow redesign
Capacity optimization and efficiency improvement
High-volume operations management
Cross-functional execution with IT
Root cause analysis and process simplification
Scalable system design

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