Product SME – Auto Claims

Product SME – Auto Claims Assured is on a mission to modernize insurance. Claims processing (i.e. should we pay this claim?), while often overlooked, is the foundation of the entire industry. It’s currently highly manual, involving phone calls, faxes, and gut instinct, costing tens of billions of dollars a year. We can do better. At Assured, we provide large insurers with the software solutions they need to win in a modern, technology-driven world. From self-service claim-filing software to backend fraud detection, we’re the engine that powers claims processing for some of the largest insurers in the world. The challenges we face are deep and diverse, from creating digital experiences that provide comfort and clarity to claimants at their most stressed and vulnerable to orchestrating large-scale ML-driven decision-making on billions of dollars of claims payments, life at Assured is dynamic, collaborative, and rewarding. Assured Insurance Technologies is seeking a Product SME to lead a comprehensive evaluation of the end-to-end auto claims process. This role will focus on understanding how claims move from First Notice of Loss (FNOL) through resolution, how decisions are made and documented, how data flows across systems, and where operational and product improvements can meaningfully impact cycle time, accuracy, customer experience, and financial performance. This role sits at the intersection of Product, Engineering and Analytics and is expected to drive meaningful, company-wide impact. WHAT YOU’LL DO… 🔍 Conduct an end-to-end review of the auto claims lifecycle Examine the full claim journey; FNOL intake, investigation, coverage evaluation, liability assessment, damages review, reserving, negotiation, settlement, and closure, identifying friction points and opportunities for automation. 🧠 Develop deep expertise in how claims decisions are made and supported by data Understand what information adjusters rely on (statements, telematics, police reports, photos, repair estimates, medical documentation, policy data), how it is structured in the system, and where gaps or inefficiencies exist. 🧩 Identify breakdowns in claim workflow and documentation Surface inconsistencies in data capture, reserve alignment, task routing, handoffs, approval processes, customer communications, or downstream reporting that affect claim outcomes. ✅ Own the integrity of core claims data across systems Ensure key indicators (coverage status, liability stance, damages exposure, reserve position, settlement status) are accurately captured and consistently reflected across product, operational, and financial views. 📐 Define standards for claims quality and defensibility Establish expectations for documentation rigor, decision rationale, reserve accuracy, communication clarity, and alignment between investigation findings and financial outcomes. 🤝 Partner cross-functionally to resolve systemic issues Collaborate with Product, Engineering, Claims Operations, Analytics, and Leadership to address root causes impacting claim efficiency, accuracy, and customer experience. 🛠️ Improve both inputs and outputs across the claims process Enhance how evidence and claim information are collected, structured, and surfaced to improve how insights are delivered through dashboards, reporting, automation workflows, and AI models. 📊 Translate insights into measurable product improvements Prioritize enhancements that reduce cycle time, improve loss ratio performance, minimize leakage, strengthen reserving accuracy, improve customer satisfaction, and increase operational efficiency. 🧭 Influence roadmap decisions with financial and operational context Clearly articulate business impact across indemnity spend, expense management, subrogation recovery, litigation exposure, adjuster productivity, and customer retention. 🎓 Serve as the internal subject-matter expert on the auto claims lifecycle Guide best practices for claim handling, documentation standards ... (truncated, view full listing at source)