Talks that move

Claims Classifier

Improving service efficiency and accuracy by automating the classification and routing of customer complaints using AI and natural language processing

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High volumes of customer interactions are manually classified, creating inefficiencies, inconsistencies, and delays in service response and resolution

WHY THIS “CLAIMS CLASSIFIER” CHALLENGE?

From manual triage to intelligent case routing

Customer service operations depend on accurate classification, yet manual processes introduce errors, slow response times, and limit scalability

Key benefits

Where service efficiency is lost in the first step of the process

Why inaccurate or delayed classification creates downstream inefficiencies across the entire service operation

Manual classification creates bottlenecks

High interaction volumes overwhelm teams, slowing down response times and increasing operational load

Inconsistent categorization reduces quality

Human variability leads to errors in routing, affecting resolution speed and customer experience

Limited scalability of service operations

Growing interaction volumes cannot be efficiently managed without automation

Delayed routing impacts resolution outcomes

Incorrect or late classification slows down the entire service lifecycle

How NTT DATA helps

01

Prepare and structure customer data

Clean, normalize, and enrich historical interaction data to ensure high-quality model training

02

Develop advanced NLP classification models

Use deep learning to understand context, intent, and linguistic variations in customer requests

03

Automate case classification and routing

Assign each interaction to the correct category in real time, reducing manual effort

04

Integrate with service workflows

Embed the model into existing systems to enable seamless operational execution

05

Continuously optimize model performance

Refine accuracy through monitoring, feedback loops, and evolving data inputs

Proven impact

Transforming service operations through intelligent automation

Results that matter

How faster and more accurate classification improves service performance end-to-end

95% accuracy within top 3 predictions

AI-driven classification significantly improves consistency and reduces routing errors

Up to 25% FTE reallocation

Automation frees resources to focus on higher-value customer interactions

~€215,000 annual cost savings

Reduced manual workload lowers operational costs associated with classification

Improved response times and service quality

Accurate routing accelerates resolution and enhances customer satisfaction

Automate your service operations with AI

Discover how to reduce effort and improve accuracy

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