Hello, my name is Pravesh Nikhare, Senior Benefits Configuration, Product Manager at Delta Intel of California. Welcome everyone. It's a pleasure to be here today to talk about a game changing innovation in dental insurance claims processing. With rule based AI. For years, the dental insurance industry has faced delays, errors, and rising administrative costs due to outdated claims processing methods. AI driven automation is now reversalizing this space, making claims processing faster, more accurate, and cost effective. In this session, we'll explore how AI, specifically rule based AI is streamlining workflows, improving compliance and enhancing customer satisfaction. By the end of this presentation, you'll have a clear understanding of how AI driven claims automation can significantly reduce manual intervention, minimize fraud and provide seamless experience for both insurers and policyholders. Let's dive in. Dental insurance claims processing has long been burdened by inefficiencies and manual bottlenecks. A single claim often requires multiple reviews, leading to delays in approvals, increased administrative workload and high costs. Insurers must navigate a complex landscape of regulatory requirements, policy guidelines and clinical documentation, increasing the risk of human error and processing inconsistencies. For policyholders, this means long wait times for claim approval and reimbursements, creating frustration and dissatisfaction. Additionally, fraud and claims. Cost insurers billions of dollars annually. Further complicating operations without automation, insurers struggle to scale efficiency, leading to a lack of transparency and operational inefficiencies. Air driven automation offers a solution, one that optimizes processing, reduces fraud, and ensures compliance, making claims handling more efficient than ever before. At the heart of this transformation is rule-based ai. Which mimics human decision making by encoding insurance policies, regulatory guidelines, and clinical best practices into structured, machine readable formats. This enables the system to evaluate claims consistently and accurately without manual intervention. One of the key components is automated claims analysis where AI cross references submitted claims with historical patterns, clinical guidelines, and policy terms to identify potential discrepancies. Fraud risk or eligibility mismatches. This not only accelerates approvals, but also ensures that insurers only pay for valid claims. Additionally, natural language processing plays a critical role in interpreting dental documentation, procedure codes, and patient histories. By standardizing diverse inputs, NLP ensures precise claim evaluation, reducing disputes and enhancing efficiency. Implementing rule based AI dramatically improves operational outcomes. One of the most compelling benefits is the acceleration of claims approval. From an average of 7 days down to just 2 days. This significant reduction is turnaround time directly impacts customer satisfaction, allowing providers to deliver timely responses and resolutions. Moreover, the automation process leads to a remarkable reduction in human errors. With AI handling data entry and analysis, the risk of mistakes is minimized by up to 90%, thereby reducing. Claim reversals and improving overall accuracy. These improvements ensure that administrative resources are allocated more effectively and efficiently, allowing teams to focus on complex cases that require human insight. The enhanced transparency provided by AI also cannot be overstated. Real time status updates, detailed audit trails, and comprehensive reporting capabilities ensure that every step of the process is visible and accountable. This operational clarity fosters trust among stakeholders. and creates a robust framework for continuous improvement. Let's look into the numbers that illustrate the AI. One of the standout benefits is that AI can automatically process 85 percent of standard claims without any human intervention. This level of automation not only speeds up the process, but also frees up valuable human resources for more strategic tasks. Processing time is reduced dramatically. With claims moving from five to seven day cycle to an average of just 48 hours. The 60 percent reduction in processing time translate into more responsive and agile operation where customer inquiries are resolved swiftly and efficiently. The quantitative benefits of these improvements are evident in both operational performances. And customer satisfaction matrix in addition to speed the cost savings are substantial by reducing manual operation processing by minimizing errors. Administrative cost drops to approximately 30%. These savings can be reinvested into further innovations or passed to customers as improved service offerings, making compelling business case for adopting rule based AI. Rule based AI brings a new level of security to dental claims processing with its real time fraud detection capabilities by analyzing patterns and identifying anomalies. AI can detect fraudulent claims within seconds, reducing fraudulent payout by up to 45 percent. This proactive approach not only saves cost, but also protects the integrity of the claims process. compliance in other critical areas where AI makes a substantial impact. This systems adaptive machine learning model continuously update to reflect new healthcare regulations and guidelines, achieving a 22 percent improvement in regulatory compliance rate. This means that insurers can be more confident in their adherence to complex regulatory framework, reducing the risk of costly penalties. The integration of predictive analytics further strengthens risk management by identifying potential compliance issues before they escalate. The AI system reduces audit related penalties by 35%. This dual focus on fraud detection and compliance creates a secure, efficient, and trustworthy environment for claims processing. Integrating AI into existing legacy systems may seem daunting, but a structured phase approach can ensure a smooth transition. The first step is a comprehensive assessment of the current infrastructure, which helps to identify critical integration points, dependencies, and potential technical constraints. The initial audit is crucial for developing a realistic roadmap for change. Once the infrastructure is mapped out, a phased implementation strategy is employed. Starting with non critical system allows the organization to test and refine the integration process without disrupting core operations. Gradually expanding the AI's reach ensures that each phase is well understood and optimized before moving on to more complex areas, thereby minimizing risk associated with a full scale rollout. Additionally, robust data migration planning is essential. This includes detailed data mapping, validation rules, and rollback procedures to safeguard against data loss. With careful planning and execution, legacy systems can be seamlessly integrated with AI technologies, setting the stage for a more efficient and reliable claims processing operation. Despite its many benefits, implementing rule based AI comes with its set of challenges. Data migration is one of the primary hurdles. Transitioning historical claims data to a new AI driven system can be complex and time consuming, requiring meticulous planning and execution to ensure data integrity and continuity. Another significant challenge is the initial investment required for AI technology. While the long term benefits in terms of efficiency, accuracy, and cost saving are substantial, the upfront cost can be a barrier for many organizations. Securing the necessary budget and resources is a critical step in making the transition to a success. Ensuring data privacy and security also presents a challenge in today's regulatory environment. With strict compliance requirements such as HIPAA, maintaining the privacy of sensitive patient data is paramount. Overcoming these challenges involves a strategic approach, combining careful planning, stakeholder buy in, and the selection of Trusted AI partners. Consider the real world example for a leading dental insurance provider that faced significant customer dissatisfaction due to lengthy claims processing time. Their average processing period was between 7 to 10 days, leading to a higher customer churn rate of 35%. The slow turnaround time was not the only impacting customer satisfaction, but also contributing to rising operational costs. The insurer deployed an advanced rule based AI system to automate claims validation, integrate real time fraud detection, and optimize payment workflows. The transformation was remarkable. Processing times were slashed to under 48 hours, leading to an 80 percent increase in customer satisfaction. 9 percent and processing costs dropped to 40%, making this case a powerful testament to the AI benefits. This case study illustrates that with the right technology and implementation strategy, even long standing industry challenges can be overcome. It highlights the tangible businesses and customer benefits that result from embracing innovation in AI solutions in claims processing. Looking ahead, the integration of emerging technologies such as blockchain and computer vision promises to further enhance the dental claims processing landscape. Blockchain technologies offer A secure, immutable ledger of claim records and ensuring that every transaction is transparent and tamper proof. This not only enhances security but also facilitates real time payment verification, fostering trust amongst all stakeholders. Computer vision is set to revolutionize the way dental images and x ray are analyzed by deploying advanced image recognition algorithms. The AI system can instantly verify dental procedures, reducing processing times by up to 75%. This technology ensures that visual data is interpreted accurately and efficiently, leading to quicker approvals and better patient outcomes. Together, these technologies complement rule based AI by adding layers of security, accuracy, and speed. They represent the next frontier in automated claims processing, promising a future where technology and healthcare converge to deliver unparalleled To summarize, rule based AI is said to revolutionize dental insurance claim processing. The technology reduces processing time by 80 percent and achieves accuracy level as high as 99. 9%, providing a clear competitive advantage in today's market. The operational benefits ranging from faster approvals and reduced error to significant cost saving are both quantifiable and transformative. Furthermore, the phased integration with legacy systems and adoption of emerging technologies like blockchain and computer vision ensures that the benefits of AI can be scaled across the organization. The measurable improvements in fraud detection, compliance and operational efficiencies Make compelling case for investing in ai. Now these take these key takeaways, underscore the transformative potential of rule-based AI in reshaping an entire industry. By embracing these changes, organizations cannot only streamline their processes, but also enhance customer satisfaction and position them themselves for future innovation. The future of dental insurance claims processing is here. And it is powered by intelligent automation. As we conclude, it's important to focus on actionable next steps for those looking to implement rule based AI in their claims processing operations. Begin by conducting a thorough audit of your claims, workflow, identify specific bottlenecks. And if inefficiencies that hinder performance and use these insights to develop a strategic roadmap for AI integration. Next, consider launching pilot programs in non critical areas. This phased approach allow you and your team to adapt. to new system gradually while minimizing risk to core operations. Establish robust data migration protocols and work closely with your trusted AI solution providers to ensure a smooth transition. These early steps are crucial to laying the foundation of a scalable, efficient and cost effective claims processing system. Finally, invest in training and change management. Equip your team with necessary skills and knowledge. To work alongside AI technologies with a clear strategy, phased implementation, and strong support, your organization will be in a good position to harness the full potential of rule based AI. Thank you for your time and attention throughout this presentation. I hope the insights shared today has sparked ideas on how rule based AI can transform dental insurance claims processing, not only in terms of efficiency, but also in enhancing customer satisfaction and overall business performance. Again, thank you for joining the session. Let's continue. Let's shape the future together.