Warranty Claims Coding
Automated warranty claims coding with NLP classification achieving 75-85% auto-coding rate and 95% consistency, reducing processing time by 90%.
Challenge
Warranty teams receive high volumes of free text claims from portals, emails, and service notes. Analysts switch between CRM and ERP to interpret issues and select codes, taking 8–12 minutes per claim. Coding varies by analyst and region, causing rework and audit gaps. Leaders lack consistent trend data to spot product issues, supplier defects, and emerging field problems.
The objective: auto-code ≥75% of claims across symptom, cause, part, resolution, and severity with ≥95% consistency; cut handling time to <1 minute per claim; deliver same day dashboards and alerts.
Solution: How AIP changed the operating model
Learning and setup
Powered by the Aftermarket Intelligence Platform AIP, the agentic solution applied its predictive multi label NLP classification, policy validation, and LLM based NLU with ontology mapping models. Training data came from historical claims and final code sets, coding guidelines and policy rulebooks, parts catalogs and product taxonomy, CRM ERP tickets, call transcripts and notes, and SME annotated samples. This enabled the AI agent to recognize free text descriptions, model and serial, product line, install and service dates, warranty tier, part IDs and SKUs, failure codes, symptom and resolution terms, region and customer, and attachments as needed.
Workflow orchestration
The AI agent reads each new claim event, extracts identifiers and key terms, and selects the correct path: verify entitlement, assign multi label codes, de duplicate entries, or open analyst review. It navigates CRM cases, ERP warranty modules, and the ontology graph in the same sequence a claims analyst would follow. Orchestration branches when confidence drops below a threshold or when policy rules fail, while logging each decision for audit and compliance.
Execution and resolution
The AI agent parses and normalizes text, extracts entities, maps terms to the ontology, classifies across symptom, cause, part, resolution, and severity, applies policy checks and de duplication, assigns codes with confidence, updates ERP warranty records and CRM cases, and posts explanations and rationales. Responses complete in seconds, and the system streams metrics to dashboards while batch jobs backfill historical claims. Exceptions such as missing model or serial, conflicting part numbers, or very low confidence are routed to analysts with full context attached.
