How to Streamline Claims Processing

When disaster strikes, every hour counts. What if complex insurance claims could be processed in hours instead of days? Drawing from my own experience as a Texas resident impacted by hurricanes, I've developed a proof-of-concept using #AzureOpenAI and #SemanticKernel to streamline property claims processing. Key Outcomes: ✅ 𝗙𝗮𝘀𝘁𝗲𝗿 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴: Automate coverage checks and policy verification, cutting cycle times from days to hours. ✅ 𝗗𝗮𝘁𝗮-𝗗𝗿𝗶𝘃𝗲𝗻 𝗔𝗰𝗰𝘂𝗿𝗮𝗰𝘆: Integrate weather data to validate damages and ensure fair settlements. ✅ 𝗥𝗮𝗽𝗶𝗱 𝗥𝗲𝗽𝗼𝗿𝘁𝗶𝗻𝗴: Generate detailed documents, recommendations, and letters on demand. This approach aims to get policyholders the support they need—faster and more reliably. Read the full article: https://lnkd.in/e7SHdn6u #Insurance #GenAI #RAG #OpenAI #MSFTAdvocate #MultiAgent

🦷 Dental support organizations (DSOs) today face intense pressure to streamline revenue cycle operations. 📊 With 60–80% of practice revenue tied to insurance reimbursements, manual RCM processes – from eligibility checks to claims posting – create bottlenecks, errors and revenue leakage. For example, industry surveys show denial management is the single most time-consuming task (76% report it as their top hassle) and even prior authorizations and benefit verifications rank highly (60% and 59%, respectively). Coupled with front-office labor shortages, this squeezes cash flow and EBITDA. Automating RCM tasks with robotics and AI is no longer optional: it’s a strategic imperative. DSOs have huge scale but also huge complexity. Submitting claims, reconciling payments and chasing patient balances can involve dozens of portals and data systems. Every manual claim entry or status check risks a typo or delay. Robotic Process Automation (RPA) can mimic what in-house staff do – logging into payer portals, copying data, and populating patient accounts – at machine speed. For instance, an RPA bot can automatically pull insurer payments from portals and match them to rendered treatments, eliminating dozens of tedious clicks. The result is fewer posting errors and faster payment cycles, enabling staff to focus on exceptions. Likewise, AI (especially NLP and machine learning) can sift unstructured data (like EOBs or clinical notes) to spot issues before they become denials. In short, automating eligibility checks, claims entry and payment posting frees DSOs and their affiliated practices from routine tasks and slashes common error rates. Key challenges in DSO RCM – high denial rates, patient collections, and complex billing – are ideal targets. On a DSO’s scale, even a 10–20% gain in collections efficiency can translate to multi-million-dollar improvements in EBITDA. RCM automation reduces cost-to-collect and accelerates reimbursements. The freed-up capacity allows staff to manage more complex, value-adding activities like tackling complicated denials and tailoring payment strategies – for example, negotiating outlier cases or improving patient engagement – rather than routine data entry. DSO executives should view RPA and AI as complementary tools in the RCM toolkit. 👇 Key use-cases include: 1️⃣ Automated Eligibility & Insurance Verification 2️⃣ Intelligent Claims Processing 3️⃣ Automated Payment Posting & Reconciliation 4️⃣ Denials Triage and Appeals 5️⃣ Automated Patient Billing & Collections 6️⃣ AI-Driven Analytics & Forecasting 💰 By embracing RPA and AI in claims processing, denial management and patient collections, DSOs can plug revenue leaks and turn administrative cost savings into EBITDA growth. 🔔 Follow me (Sina S. Amiri) for more insights on transforming dental RCM through AI and automation. #Healthcare #Dental #Technology #RevenueCycleManagement #ArtificialIntelligence

⏱️ Scaling Claims Transformation: Lessons from a 30% Time Reduction Imagine cutting claims processing time by 30%—what impact would that have on your organization? 🚀 Having led Global Claims Business Performance at AIG, I’ve seen that scaling claims transformation goes beyond technology. It requires synchronizing innovation, people, and processes. 📖 Here’s how one global insurer made it happen: 🤖 1. Automation in action – AI-driven triaging and automated workflows reduced manual steps and streamlined low-complexity claims. 📊 2. Data integration at its core – Merging fragmented systems created better insights and enhanced customer experiences. 🌎 3. Regional customization – Tailored approaches—such as compliance-focused strategies in Europe and relationship-driven solutions in LatAm—ensured successful implementation. 💡 The results: ✔️ Faster claims resolutions, driving higher customer satisfaction. ✔️ Substantial cost savings across operations. ✔️ A repeatable model for innovation and growth. ✨ Key takeaway: Successful claims transformation demands a clear vision, adaptable technology, and localized execution. What’s your biggest challenge—or success—when scaling claims transformation? Let’s collaborate on ideas to drive the industry forward. 💬 #InsuranceInnovation #ClaimsEfficiency #AIInInsurance #GlobalTrends #LeadershipInInsurance #InsuranceCareersMonth