The Challenge: Inefficient Manual Processes
In today’s fast-paced customer service landscape, contact centers struggle with manual, time-consuming processes. Traditional human intensive support methods—such as reviewing emails, categorizing requests, and escalating cases—lead to delays, errors, and customer dissatisfaction. Managing credit card disputes is a complex process requiring rapid resolution and accurate handling.
What sets Agentic AI Apart?
Agentic AI stands out from previous bot generations due to its dynamic, human-like reasoning powered by Large Language Models.
Unlike traditional bots that follow rigid, pre-defined conversation flows—requiring developers to anticipate every possible interaction—Agentic AI adapts in real time. It leverages enterprise knowledge and stores customer data to generate context-aware responses, ensuring fluid and natural interactions.
With the ability to break down complex tasks, autonomously determine the most efficient resolution path, and continuously refine its approach, Agentic AI mirrors human decision-making. This unparalleled flexibility allows it to think, respond, and react in real time, transforming how businesses engage with customers.
The Solution: AI + RPA for Faster Resolutions
To address these challenges, we implemented an Agentic AI-driven, RPA-powered dispute management system that streamlines dispute handling and enhances customer interactions. By integrating Generative AI and Intelligent Automation, we enable real-time ticket classification, sentiment analysis, and automated resolutions.
Process Flow
Technical Workflow: A Seamless Automation Process
1. Customer Dispute Submission
- A customer submits a dispute request via email or web portal.
2. Automated Data Extraction
- An RPA bot scans email, extracting transaction details and customer information using Amazon Bedrock AI.
3. AI-Powered Sentiment Analysis
- AI evaluates sentiment to prioritize urgent cases (e.g., fraud claims marked as high priority).
4. Dispute Validation & Case Creation
- RPA validates dispute details by matching transaction data with banking records via a third-party API.
- If valid, a dispute case is auto-created in the case management system (Zendesk).
5. Automated Customer Communication
- AI generates an initial response with resolution steps based on SLA guidelines from the knowledge base.
- RPA sends an email update to the customer, reducing response times.
6. Final Resolution & Closure
- Once the investigation is complete, the AI-powered agent generates a final resolution response.
- RPA updates the case and notifies the customer, ensuring transparency and efficiency.
The Impact: Faster Processing, Higher Satisfaction
Reduction in Processing Time: Automation accelerates dispute handling, reducing delays.
Enhanced Accuracy: AI minimizes errors in data extraction and case classification.
Improved Customer Experience: Faster resolutions lead to higher customer satisfaction.
Scalability: The solution adapts to high volumes of requests without additional workforce requirements.
Conclusion: The Future of Contact Centers
With AI and automation, contact centers can shift from reactive support to proactive, intelligent customer engagement. The AI-Powered Contact Center Agent revolutionizes dispute resolution, ensuring efficiency, accuracy, and customer trust in every interaction.
Topic: Blog
