SBIR Phase I: Intelligent Interactive Guidance System for Litigated Insurance Claims

SBIR第一期：保险理赔智能互动引导系统

• 批准号: 2329603
• 负责人: James Chapman
• 金额: $ 27.5万
• 依托单位: MAYFAIR GROUP LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-15 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2329603&HistoricalAwards=false
• 关键词: SBIR; Phase; Intelligent; Interactive; Guidance

This Small Business Innovation Research (SBIR) Phase I project enhances the efficiency, fairness, and cost-effectiveness of the United States' property and casualty insurance claims processes. This project aims to develop an advanced, artificial intelligence (AI) powered guidance system that will transform how litigated insurance claims are managed and resolved. By enhancing the decision-making process of claims professionals with automated, evidence-backed guidance, the system will significantly reduce the time and expense currently required to resolve claims, resulting in quicker payouts to claimants and decreasing the burden of legal costs. The system's innovative approach will assist in identifying critical case information, supporting claim professionals in making more informed decisions. The project has the potential to improve the overall transparency and reliability of the claims litigation processes, engendering greater trust in the insurance system. Additionally, by streamlining operations, it could lead to more efficient use of resources within the insurance industry, lowering insurance premiums for consumers and businesses. This SBIR Phase I project represents an opportunity to significantly improve the processing and handling of litigated insurance claims. The project’s research objectives include the development of a novel approach for information extraction from massive unstructured data collections typical in insurance claims and summarization frameworks for presenting the extracted information, enabling a concise yet comprehensive view of complex claims data. The project aims to design a visualization interface that aids understanding and facilitates more informed decision-making by claims professionals. The research applies cutting-edge AI and machine learning techniques to these objectives, expanding past the boundaries of current capabilities in data analytics within the insurance industry. The anticipated technical results include demonstrating the feasibility of this innovative system to quickly and accurately present relevant decisional information from a broad array of data, providing users with essential insights for making decisions. By improving how information is processed, summarized, and presented, the project is expected to lead to better, faster decisions in litigated insurance claims management, setting a new standard for technological applications in the field.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这项小型企业创新研究（SBIR）I期项目提高了美国财产和休闲保险索赔流程的效率，公平性和成本效益。该项目旨在开发高级，人工智能（AI）有动力的指导系统，该系统将改变如何管理和解决诉讼的保险索赔。通过通过自动化，证据支持的指导加强索赔专业人士的决策过程，该系统将大大减少目前解决索赔所需的时间和费用，从而使索赔人的支出更快，并减少了法律成本的燃烧。该系统的创新方法将有助于确定关键案例信息，并支持索赔专业人员做出更明智的决定。该项目有可能提高索赔诉讼过程的总体透明度和可靠性，从而提高对保险系统的更大信任。此外，通过简化运营，它可能会在保险行业内更有效地利用资源，从而降低了消费者和企业的保险费。这个SBIR I期项目代表了一个机会，可以显着改善诉讼保险索赔的处理和处理。该项目的研究目标包括从保险索赔和摘要框架中典型的大规模非结构化数据收集中开发新的信息提取方法，以呈现提取的信息，从而对复杂的索赔数据进行简洁而全面的看法。该项目旨在设计一个可视化界面，该界面有助于理解并促进索赔专业人员更明智的决策。该研究将尖端的AI和机器学习技术应用于这些目标，从而超越了保险行业中数据分析当前功能的边界。预期的技术结果包括证明这种创新系统的可行性，可以从广泛的数据中快速，准确地提供相关的决策信息，从而为用户提供做出决策的基本见解。通过改善如何处理，汇总和介绍信息，预计该项目将在诉讼的保险索赔管理中做出更好，更快的决策，为现场的技术应用树立新的标准。该奖项反映了NSF的法定任务，并认为通过使用该基金会的智力和更广泛的Impact Impact Impact Impact审查Criteria，通过评估的支持值得一提。