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Warranty Analytics
At Nihilent we partner with organizations to improve their Warranty Management performance with SightN2™ for Warranty Analytics. This ground-breaking, pre-built solution optimizes warranty claims analysis using a patented Control Chart Automation Process. We can help you deliver real-time analysis and expanded insights customized to your organization that improves cost management, profitability, and customer satisfaction.
SightN2™ for Warranty Analytics solution automatically ingests the heterogeneous claims data from disparate sources to aggregate and analyze trends in warranty claims and processing.
Our advanced analytics solutions include:
Text Analytics: Use all data at your disposal by capturing meaningful information from comment fields and notes from service technicians and customers. Our solution leverages advanced natural language processing and text analytics to find new trends hiding in plain sight and leverage the data you are already collecting in the claims process.
Fraud Analytics: Proactively identify fraud and only approve valid claims to reduce exposure and minimize costs. Rest easy with our automated monitoring. Our solution customizes the predictive model that identifies such fraud and continues to learn and improve based on your data.
Claim Forecasting: Manage your warranty reserve with data-driven confidence. Our solution models your sales and claim processes to accurately predict future claims.
Outlier Detection: Let engineers focus on engineering and quality instead of reporting and data mining. We use sophisticated techniques to consistently and reliably identify outliers and new trends hidden in your data.
Key Benefits:
Detect issues early and determine root causes in order to develop timely mitigation strategies:
- Reduce legal risk.
- Increase accuracy of capital reserves required for warranty claims.
- Enhance the quality of products through design evolution.
- Increase efficiency in supply chain management.
- Decrease warranty costs.
- Increase customer satisfaction.