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AI-Powered Claims Automation: Revolutionizing Warranty Management with AI
Warranties are standard for most mechanized products, providing customers with options for repair, replacement, or refunds. Research shows that warranty claims and associated service costs typically account for 2% to 15% of net sales. For large companies, this can mean billions of dollars in annual expenses. Even for medium and small manufacturers, this cost has a considerable impact on the bottom line. Gone are the days when warranty claims were manually assessed, and the details recorded and processed on paper. Original Equipment Manufacturers (OEMs) can now leverage AI-powered tools to streamline operations, enhance efficiency and accuracy, reduce manual effort and costs, and boost customer satisfaction. Additionally, automating workflows with AI also improves the ability to detect and eliminate fraudulent claims. Claims automation ensures a faster claims procedure, enhanced fairness, personalization, and easy availability. With minimal to no requirement for human intervention, the role of AI in claims significantly reduces errors and redundancies, ultimately resulting in warranty efficiency improvement. Tavant’s TMAP Warranty.AI: A Game-Changer in Warranty Management Tavant’s TMAP Warranty.AI is designed to help OEMs navigate the complex world of warranty claims with ease. Powered by AI, this solution reduces warranty costs by up to 5%, automates and streamlines processes, and improves after-sales service—leading to enhanced customer satisfaction and a significant return on investment (ROI). Suspect Claim Analytics: Suspect claims are managed efficiently through a systematic process of verifying and flagging suspicious claims, real-time claim scoring, automatic claim approval, dealer rankings, image-based anomaly detection, and rankings-based warranty audits. QA Code Predictions: Through predictive analysis, the tool accurately forecasts the likelihood of defects or failures in different products with the help of symptom code prediction, defect code prediction, remedy code prediction, and warranty system integration with multi-language support. Peer Averaging: Through labor cost analysis, labor hour clustering, parts claims clustering, and cluster value comparison, the tool helps competitor analysis for establishing benchmarks in warranty claims. Warranty Analytics: This feature covers warranty metrics and analysis of channel, claim, and return of parts. Additionally, analyst performance, warranty registration, dealer performance, supplier recovery, and claims forecast are other aspects analyzed in detail. Machine Failure Cluster: From cluster size monitoring to assessment of failure metrics and real-time product monitoring, it is possible to understand the root cause of machine faults better than ever before. Service Parts Management & Contract Analysis: Through a set of operational metrics, portfolio & pricing analysis as well as parts & service demand forecasting, the tool efficiently handles contracts and service allocation. Quality & Reliability: Weibull analysis, quality KPIs, and product quality systems are important components in ensuring the quality and reliability of outputs. Intelligent Search: Intelligent search forms the core of any AI tool, and with a focus on warranty claims, features like contextual search, Q&A, and knowledge management play a key role in the verification process. Field Service Analytics: A range of fieldwork analyses including service ticket prioritization, trend analysis, work order & inventory report generation, and service technician performance analysis, among others. Dealer Certification: Service & sales certification, performance-based dealer classification, points-based categorization, category-based incentive schemes, and dealer business improvement identification The Power of AI in Claims Automation Tavant’s TMAP Warranty.AI can automate and streamline warranty claims with incredible efficiency through detailed and fast data analysis, helping OEMs make real-time, data-driven decisions. As TMAP Warranty.AI continues to learn from new data, its performance improves over time, further enhancing the warranty management process. Key Benefits for OEMs Using TMAP Warranty.AI: Improved Efficiency and Cost Savings: Automation eliminates routine tasks, enabling faster and more accurate claims handling. TMAP Warranty.AI automates routine tasks involved in the process and encourages decisions backed by accurate data, businesses can expect efficiency gains, lower expenses, cost savings in warranty, and better customer satisfaction. Enhanced Customer Service: Through AI-powered automation in TMAP Warranty.AI, expect claim settlement to be speedy and accurate. Customers will appreciate the lower waiting period and the hassle-free resolution process that increases brand loyalty and trust. Future trends in warranty automation Warranty management no longer needs to be a manual, labor-intensive process. Tavant’s TMAP Warranty.AI is an innovative, advanced solution designed to automate claims. The tool delivers automation excellence through its ability to learn from data, making it a critical asset in modern warranty management. AI-powered solutions like Warranty.AI go beyond offering the convenience of automating tasks – they offer intelligent solutions backed by identifying patterns and trends and offering data-driven insights. While inspired by traditional manual processes, these advanced tools streamline the entire system, enabling faster and more accurate claims resolution. By leveraging data-driven approaches, OEMs can handle a higher volume of claims with precision, enhancing both operational efficiency and customer satisfaction. By adopting AI early, OEMs can not only reduce costs but also deliver faster, more reliable service, making AI a crucial investment for the future of warranty management. Reach us at [email protected] to schedule a demo on TMAP Warranty.AI
Harnessing the Power of IoT Data: A Holistic Approach
In our hyper-connected world, the Internet of Things (IoT) isn’t merely a buzzword—it’s a transformative force reshaping industries and business landscapes. At its core lies a treasure trove of data generated by sensors, devices, engines, and machines. But here’s the untold story: Historic IoT data, when combined with insights from other systems, becomes a game-changer. The Underutilized Library of Data Challenge: Companies invest substantial resources in IoT and Telematics hardware, software, and data connectivity. Yet, all too often, the historical data collected remains underutilized. It’s like having a vast library of books but only reading the latest bestsellers. Solution: Enter IoT data analytics. By delving into historical data, companies can uncover patterns, correlations, and anomalies. Predictive maintenance becomes a reality—machines signal when they need attention before they break down. But here’s where the magic happens: Imagine joining this historic data with insights from other critical systems. The Power of Integration CRM (Customer Relationship Management): Scenario: Your sales team logs interactions, customer preferences, and feedback. Integration: Combine CRM data with historic IoT data. Suddenly, you understand how equipment performance impacts customer satisfaction. You tailor service offerings based on usage patterns. You increase dealer sales opportunities by understanding customer use history and uncovering their needs proactively. Parts Management and Warranty Systems: Scenario: Spare parts inventory management is a puzzle. Overstocking ties up capital; understocking leads to downtime. You see an uptick in parts use but can’t correlate it. Integration: Historic IoT data reveals which components fail most frequently. Now, your parts management system stocks intelligently. Predictive maintenance reduces emergency orders. Warranty costs are controlled. Proactive product improvement becomes a reality! Pricing Systems: Scenario: Pricing decisions are often gut-driven or market-based. Integration: Overlay historic IoT data. Understand how equipment usage affects costs. Optimize pricing based on real-world performance. 3.Beyond Silos: Holistic Insights Challenge: Businesses often operate in silos—departments, regions, and customer segments isolated from one another. Solution: IoT data bridges the gaps. Imagine an agricultural equipment manufacturer learning that a specific tractor model excels in vineyards but struggles in wheat fields. Armed with this insight, they fine-tune their offerings. Dealers personalize service recommendations based on usage patterns. Customers benefit from products designed for their unique needs. How Do You Start? The challenge of unlocking historic data’s benefits can be daunting, but you know your high impact use case already, don’t you? Take a moment, write it down, and consider all the platforms and systems in your organization that hold valuable information. Now envision the power of bringing all that data together to solve your problem! Find a trusted partner who can guide you through this journey and help you fast-find the ever-returning ROI that will benefit your business for years to come. Conclusion: The Data-Driven Future IoT data isn’t just about sensors and connectivity; it’s about unlocking actionable intelligence. As businesses embrace data analytics, they move from reactive to proactive, from isolated to interconnected. So, next time you see a sensor blinking quietly in the corner, remember—it’s not just collecting data; it’s shaping the future of business. About the Author: Jon Kent lives in the Metro Atlanta area with his family. He is an IoT, Telematics, and Field Service Technology thought leader and enthusiast. His 20+ year career experiences have brought him to Tavant, a global technology organization with U.S headquarters in Santa Clara, CA. Jon works within the Tavant TMAP Product Group, that focuses on finding value in a company’s data across any number of systems, including IoT / Telematics, CRM, ERP, Warranty, Parts, Service Case, Contract Management, and Field Service. For more information or to schedule a conversation, please visit: TMAP | Tavant
