Sutherland Transforms Credit Card Dispute Resolution for a Leading Bank, Achieving 60% Reduction in Manual Effort and $2.4M in Cost Savings

Client Overview

The client is a prominent financial services provider specializing in credit card solutions, personal loans, and financial products, serving millions of customers across the United States. With a strong focus on non-prime and near-prime consumers, the company plays a critical role in expanding credit access while maintaining compliance with stringent financial regulations.

The Challenge

Manual Processes, Rising Volumes, and Compliance Risks Constrained Dispute Operations

As transaction volumes surged, the client required a more efficient and scalable dispute resolution framework to handle chargebacks, minimize financial losses, and maintain strict regulatory compliance. Credit card disputes present a significant operational and financial challenge for issuers, demanding speed, accuracy, and compliance adherence to mitigate risks and prevent losses.

However, the client’s manual dispute resolution process created multiple inefficiencies:

• High Manual Effort & Processing Delays – Traditional dispute handling relied on manual reviews, resulting in longer cycle times and growing backlogs.
• Error-Prone Investigations – Inconsistent documentation and human errors increased compliance risks, leading to potential financial penalties.
• Rising Dispute Volumes – As transaction activity grew, the client struggled with scalability, requiring automation to efficiently manage dispute resolution.
• Regulatory Compliance Pressures – Adherence to strict card network and financial regulations (Regulation E & Z) demanded improved tracking, auditability, and accuracy.

To address these challenges, the client sought a fully automated, AI-powered dispute resolution framework that would enhance processing speed, reduce errors, ensure compliance, and scale efficiently with growing transaction volumes.

Sutherland was engaged to transform dispute management through intelligent automation, AI-driven decisioning, and compliance-focused workflows, enabling faster resolutions, improved accuracy, and a superior customer experience.

Sutherland Solution

AI-Driven Dispute Resolution for Greater Speed, Accuracy, and Compliance

Sutherland implemented an intelligent, AI-driven dispute management system that leveraged automation, robotic process automation (RPA), and advanced analytics to enhance accuracy, speed, and regulatory compliance while reducing operational effort.

1. AI-Driven Dispute Case Prioritization
   Sutherland introduced AI-powered prioritization models to automatically categorize disputes based on risk level, transaction patterns, and historical data. Machine learning algorithms flagged high-risk cases for expedited investigation, enabling faster resolutions and more effective fraud detection.
2. Robotic Process Automation (RPA) for Investigation & Documentation
   To eliminate manual inefficiencies, Sutherland deployed RPA bots to extract, validate, and cross-check dispute-related data across multiple systems. The automation streamlined chargeback initiation, response submissions, and documentation tracking, significantly reducing human error and processing delays.
3. Real-Time Compliance Tracking & Audit Readiness
   Sutherland developed a real-time compliance dashboard to monitor regulatory adherence for Regulation E & Z. Automated audit logs provided full transparency and traceability, ensuring seamless regulatory reporting and audit readiness while mitigating compliance risks.
   
4. Enhanced Customer Communication & Faster Resolutions
   To improve customer experience, Sutherland integrated self-service dispute portals, allowing customers to track and manage claims with ease. AI-powered chatbots provided real-time dispute updates, reducing dependency on call center agents and enhancing resolution speed.

By automating dispute workflows, strengthening compliance oversight, and enhancing customer interactions, Sutherland transformed the client’s dispute resolution process – delivering faster processing, improved accuracy, and scalable efficiency in a highly regulated financial environment.

The Outcome

Scalable Efficiency, Enhanced Accuracy, and Full Regulatory Confidence

Sutherland’s AI-driven dispute resolution framework delivered measurable improvements in efficiency, accuracy, compliance, and cost optimization, positioning the client for long-term operational resilience:

• 60% Reduction in Manual Effort – AI-driven automation eliminated repetitive, labor-intensive tasks, enabling internal teams to focus on high-value case management, strategic oversight, and customer engagement.
• 99.5% Accuracy in Dispute Processing – Advanced machine learning algorithms and RPA-powered validation enhanced precision, minimizing processing errors and ensuring strict regulatory adherence.
• $2.4M in Cost Savings Over Three Years – Process optimization and automation-led efficiencies significantly reduced operational overhead, delivering substantial long-term financial benefits.
• 40% Acceleration in Dispute Resolution Timelines – AI-enhanced case triaging and automated workflows streamlined investigations, expediting chargeback resolutions and improving customer satisfaction.
• 100% Regulatory Compliance & Audit Readiness – AI-driven compliance tracking and real-time documentation ensured seamless adherence to Regulation E & Z, mitigating legal risks and eliminating regulatory penalties.

By integrating AI, automation, and intelligent compliance management, Sutherland redefined the client’s dispute resolution process, driving scalability, cost efficiency, and enhanced customer trust in a highly regulated financial landscape.

That’s digital outcomes delivered!

With Sutherland’s AI-powered automation and workflow optimization, the client transformed its dispute resolution process, achieving higher efficiency, cost savings, and improved compliance.

By eliminating manual errors, accelerating resolution cycles, and optimizing compliance tracking, the client successfully built a future-ready, scalable dispute management framework.