Hi, my name is PN Senior Benefits Configuration Product Manager at Delta Dental of California. It's a pleasure to be here today to discuss how rule-based AI systems are transforming the way dental insurance claims are processed. As we know, insurance claims can be tedious, time consuming, and prone to errors, but AI driven automation is revolutionizing the space today. I'll walk you through. The key components of rule-based ai, its operational mechanisms and the benefit it offers to various stakeholders and some of the challenges organizations need to overcome when implementing these systems. By the end of the presentation, you'll see why AI is no longer just an option, but necessity for the future of dental insurance claims processing. Let's dive in and explore exciting transformation. Traditional claims processing involves extensive paperwork, manual data entry, and human decision making, leading to inefficiencies and inconsistencies, errors and delays, not only frustrate patients and providers, but also increase administrative costs for insurers. Rule-based AI introduces a structured approach to automate and standardize these processes. AI achieves this through four key functions. Rule ENC coding. It converts complex policies into structured machine learning, readable rules, ensuring compliance and insurance regulations, pattern recognition. AI can analyze past claim data to detect common trends and improve the accuracy of claims assessment. Consistency, like human assessors, AI applies the same decision criteria to every claim, eliminating bias and variability. Adaptability. Adaptability. As policies and regulations change, AI driven systems can update their rule sets dynamically without major disruptions. These capabilities collectively streamline claims processing, reduce costs, and enhance the overall efficiency of dental insurance workflows. For AI to function effectively in dental insurance claims processing, it relies on three essential components, a policy driven rule engine, a multi-stage claims validator, and an advanced analytics engine. These components work together to ensure accuracy, efficiency, and compliance. the policy driven rule engine transform. Insurance policies into structured algorithmic rules. It codifies eligibility criteria, current limitation and reimbursement policies, ensuring that every claim is processed based on predefined guidelines. This minimizes discrepancies and ensures fairness in decision making. The multi-stage claim validator automates the validation process, checking each claim against multiple criteria such as patient eligibility, treatment history, and policy terms. Meanwhile, the advanced analytics engine leverages AI and machine learning to flag potential fraud, identify anomalies, and optimize processing efficiency. Together these components create a seamless, highly efficient claims management system, and we understand the core components. Let's break down how rule-based AI actually processes claims. The workflow can be divided into four main stages, each improving efficiency and reducing manual interventions. The first step is claim submission and initial processing where AI validates patient and provided details, ensuring eligibility before proceeding next. The system applies predefined rule, application and validation, analyzing treatment codes and checking benefit calculations, and verifying clinical necessity. This eliminates the need of manual cross-referencing. In the cross-checking against previous treatment stage, AI ensures that claim aligns with the patient dental history and treatment patterns. Finally, frequency limitation processing, which enforces policy restrictions such as annual visits, cap, or lifetime maximums. The structured approach ensure that claims are handled quickly, accurately, and in compliance with insurance policies. Tough rule-based AI on dental claims processing is profound. These systems significantly reduce manual work and improve accuracy and accelerate decision making. Studies show that AI powered claims processing can reduce administrative cost by 50% while improving accuracy rates. By up to 30%. One of the key benefits is accuracy improvement. By applying standardized rules and validation criteria, AI ensures that claims are processed correctly the first time, reducing disputes and range submissions. Processing time is also dramatically reduced with approvals happening in us instead of days or weeks. Ultimately, this technology benefits all stakeholders by reducing costs, minimizing delays, and enhancing trust in the insurance process. With fear, manual errors and greater consistency, both patients and healthcare providers experience a smoother claims experience. Compliance with insurance regulations and industry standards is critical for insurancers. Rule-based AI ensures that claims adhere to American Dental Association, a DA guidelines, HIPAA regulations, and state specific insurance policies. These systems are designed to adapt to evolving laws and prevent compliance violations. The ability to dynamically update rule sets in response to regulatory changes is a game changer. Traditional claim system require extensive manual updates leading to delays and inconsistencies. AI driven rule engines, however, can seemingly integrate new policies, dental procedure codes, and reimbursement criteria in real time. Additionally, the system enhance compliance by providing automated audit trails, ensuring that every decision made by the AI is traceable and justifiable. This not only reduces legal risk of insurers, but also fosters greater transparency and trust in the claims process. Rule-based AI benefits multiple stakeholders from insurers and policy holder to healthcare providers. Insurers experience a 50% reduction in processing cost while managing a higher volume of claims with existing resources. Automated processing enables 24 7 claim handling. Significantly reducing turnaround times for policy holders. Faster approvals and greater transparency improve the customer experience. AI ensures that claims decisions are based on clear rule-based criteria, minimizing confusion and frustration. Policy holders can also receive real time updates. On the claim status, reducing the need for follow ups. Healthcare providers also benefit as AI-driven claims Processing leads to faster reimbursement and fewer rejected claims by reducing administrative burdens. Providers can focus on patient care rather than paperwork, despite its many advantages. Implementing rule-based AI in claims processing present several challenges. The initial setup cost can range from 200,000 to 500,000, making it a significant investment for insurers. Additionally, integration with existing legacy system can take up to six to 12 months. Another limitation is the risk of system errors. While AI can process structured claims efficiently, unusual or incomplete claims may still require human intervention. Striking the right balance between automation and human oversight is essential to avoid incorrect denial or misinterpretations. Lastly, ethical considerations must be addressed. AI systems must be designed to prevent bias and ensure fairness in decision making. Transparency in AI driven decisions is crucial to maintain trust and regulatory compliance. The future of AI in dental claims processing is incredibly promising. Emerging technologies like natural Language Processing NLP can enable AI to interpret clinical nodes while deep learning can analyze dental x-rays to assess. Treatment necessity. Additionally, blockchain integration could enhance transparency and security in claims documentation. Beyond dental insurance, AI framework can be expanded to other healthcare domains, including medical, pharmaceutical, and behavioral health claims. Processing these cross-industry applications could create more unified AI powered healthcare reimbursement system. Predictive analytics will also play a key role allowing insurers to detect fraudulent claims, pattern, assess treatment, risk factors, and forecast patient outcomes with greater accuracy. As you can see in this graph, AI is trending and 90% of the dental insurance companies will adopt, AI by 2028. In conclusion, rule-based AI systems are transforming dental claims processing to improve efficiency, accuracy, and compliance. With AI driven automation, processing times are reduced by 50%, and error rates are minimized, creating a more streamlined and reliable system. As AI technology continues to evolve its role in healthcare, financing and insurance administration will only grow the future holds exciting possibilities, and from AI driven imaging analysis to blockchain. Powered claims verification. Thank you for your, thank you for your time and attention. Hope you liked the session.