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Transforming Dispute Management System With ServiceNow AI and Automation Solution | A Case Study

BFSI app icon representing ServiceNow AI and Automation solutions for enhanced financial services efficiency.

85%

Reduced manual case triage

99.9%

Achieved data consistency

70%

Document processing time reduced

Client Overview

A leading financial institution in the US was struggling with inefficiencies in handling Visa card transaction disputes, including unauthorized charges, chargebacks, and fraud-related claims. Their dispute management process was heavily reliant on manual workflows, leading to delays, high operational costs, and compliance risks. The absence of a centralized system further exacerbated the issue, making it difficult to track disputes, ensure accurate resolution, and maintain customer satisfaction.

LMTEQ’s ServiceNow team was brought in to revolutionize the client’s dispute management process through AI-driven automation, workflow optimization, and seamless core banking integration.

Objective

The primary goal of this transformation was to streamline and accelerate dispute resolution while ensuring compliance with Regulation E (Reg E) and Regulation Z (Reg Z). Specifically, the institution aimed to:
  • Reduce dispute resolution time by automating workflows and eliminating manual bottlenecks.
  • Enhance fraud detection using AI-driven predictive analytics to prioritize high-risk disputes.
  • Improve customer satisfaction (CSAT) by offering self-service options and increasing transparency in dispute resolution.
  • Lower operational costs by minimizing manual intervention and optimizing resource allocation.
  • Ensure regulatory compliance by embedding SLA tracking and audit capabilities into the workflow.

Challenges in Dispute Management

1. Fragmented Dispute Handling Across Multiple Systems

Customers could initiate disputes via various channels, including bank portals, contact centers, and in-branch visits. However, dispute forms were only reflected in either the bank’s system or Visa’s system, leading to manual synchronization efforts, processing errors, and delays.

2. Slow Manual Processing & Case Resolution

Due to the lack of automation, disputes were manually classified, verified, and routed to appropriate teams. This resulted in delayed resolutions, often exceeding SLA requirements.

3. High Contact Center Workload

With no self-service capabilities, customers had to contact support for updates, significantly increasing call center volumes and operational costs.

4. Limited Fraud Detection Capabilities

Fraudulent dispute claims required extensive manual verification, slowing down the resolution and increasing financial losses due to undetected chargebacks.

5. Compliance & SLA Management Risks

The institution struggled to track dispute case statuses efficiently, making it difficult to meet the required regulatory timelines and maintain compliance.

Overcoming the Challenges (Technical Implementation)

Implementation

  • ServiceNow AI-based categorization was applied to classify disputes into fraud-related, transaction errors, chargebacks, and merchant disputes based on keywords, transaction metadata, and customer history.
  • A risk-scoring model was deployed to prioritize high-risk cases by analyzing:
    • Historical fraud patterns
    • Merchant dispute frequency
    • Customer transaction behavior

Outcome

  • Reduced the need for manual case triage by 85%.
  • Allowed high-risk fraud cases to be flagged and escalated instantly, reducing financial exposure.

Implementation

  • ServiceNow Integration Hub was leveraged to establish API connections with the client’s core transaction system and Visa system to get details such as intake questionnaires, reason-code mapping, and chargeback eligibility.
  • These connections ensured bi-directional synchronization between the financial institution’s internal database and Visa’s dispute portal.

Outcome

  • Eliminated manual data entry and ensured that dispute status updates were reflected in real-time across Visa and core banking systems.
  • Achieved 99.9% data consistency between platforms, reducing processing errors.

Implementation

  • AI-based ServiceNow Document Intelligence (DocIntelligence) was deployed to extract key details from:
    • Dispute claim
    • Bank statements
    • Supporting documentation (receipts, invoices, emails, etc.)
    • Transaction references, timestamps, merchant details, and claim justifications.
  • These information is used to identify discrepancies in merchant dispute claims and flag inconsistencies for manual review.
  • Automated data validation and enrichment workflows ensured that extracted data was correctly mapped to the dispute case within ServiceNow.

Outcome

  • Reduced document processing time by ~70%.
  • Achieved 98% accuracy in automated data extraction, minimizing the need for manual verification.

Implementation

  • Personalized dispute tracking dashboards were integrated within the customer self-service portal to provide real-time updates on case progress.

Outcome

  • Improved customer satisfaction (CSAT) by 22%, with real-time dispute tracking reducing frustration.

Implementation

  • ServiceNow Flow Designer was configured to automate case routing and approval workflows.
  • Automated dispute case allocation based on:
    • Dispute complexity and category (fraud, chargeback, etc.).
    • Agent expertise and workload balancing.
    • Regulatory SLA deadlines (Reg E & Reg Z compliance monitoring).
    • Known fraudulent transaction patterns.
    • Customer historical disputes (repeat offenders flagged automatically).
  • Automated SLA monitoring & alerts:
    • Escalation triggers were set up for cases nearing SLA breach, ensuring proactive resolution.

Outcome

  • Reduced manual case routing time by 85%, expediting dispute handling.
  • Achieved 99% compliance with SLA deadlines, mitigating regulatory penalties.

Enhanced Technical Security & Compliance Measures

  • AES-256 encryption was applied to dispute-related customer data stored within ServiceNow.
  • Role-Based Access Control (RBAC) ensured that only authorized personnel could access or modify dispute records.
  • Automated audit trails logged every dispute action for regulatory compliance.
  • Multi-factor authentication (MFA) was enforced for dispute resolution team logins.

Key Takeaway

With LMTEQ’s expertise in AI-driven dispute management and ServiceNow automation, the financial institution successfully transitioned from a manual, fragmented process to a fully integrated, intelligent dispute resolution system.

The implementation of AI, workflow automation, and real-time banking integration not only reduced resolution time and operational costs but also enhanced fraud detection, improved compliance, and elevated the customer experience.

By leveraging ServiceNow’s AI-powered dispute management solution, our ServiceNow experts empowered the institution to handle disputes more efficiently, ensuring scalability, transparency, and long-term business growth in the ever-evolving BFSI landscape.

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