Introduction
Warranty management is a critical function that requires identifying and resolving customer complaints efficiently. However, manual processes can lead to errors, delays, and increased costs. Machine learning (ML) offers a promising solution by analyzing data from various sources, including claims history, customer feedback, and operational metrics.
Machine Learning Applications in Warranty Management
Some examples of ML applications in warranty management include:
- Customer sentiment analysis to identify issues and prioritize claims
- Predictive modeling for determining the likelihood of a claim being approved or denied
- Automated anomaly detection for identifying unusual patterns in claims data
Case Study: Using Machine Learning to Improve Warranty Claims Processing Time
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