Published Paper Details:

In response to evolving customer needs, insurance organizations are modernizing their processes, particularly in the health sector and emphasize claims processing. By integrating various stakeholders such as clinics, physicians, and security networks via cloud technology, data flow is improved, facilitating faster case approval. Challenges like data breaches and lack of transparency are addressed through proposed cloud-based solutions for secure and transparent claims administration. However, ensuring the trustworthiness of system users remains a concern. The research focuses on developing a cloud-based system prioritizing simplicity and trustworthiness for secure and transparent health insurance claims processing. Key steps in automating insurance claim processing leveraging cloud-based technologies and machine learning are outlined, including self-service FNOL intake, Intelligent Document Processing (IDP), Smart Claim Triage with Predictive Analytics, and evaluation using ML. The proposed model Hybrid Convolutional Long Short Term Memory (HCLSTM) aim to enhance injury analysis within the insurance claim process, providing deeper insights and improving accuracy.