Large insurance companies have to manage a massive amount of unstructured data in the form of documents, invoices, images, conversations and communications between clients and their claims management records. This adds complexity when trying to automate and scaling such processes.
The insurance claims management system is embedded with Multiple AI models, based on State of the Art LLMs (Large Language Models), fine tuned with NLP techniques for healthcare data and specifically trained for medical content in different languages. The AI models pre-trained with medical data about global hospitals, International Disease Classification (ICD), doctors and medications progressively learns how to process medical documents.
More than 60% of the Claims management process can be effectively automated: new document formats were automatically detected and processed without manual intervention, while increasing the customer satisfaction by several points, reducing up to 70% of the time to process a medical claim process and reducing costs dramatically.
From claims management processing and risk underwriting to customer support and fraud detection, these technologies offer innovative solutions to enhance efficiency, accuracy, and customer experience while ensuring regulatory compliance. Let's explore some specific examples of how AI and NLP can be applied in the insurance industry.
Claims Fraud Investigation: AI and NLP technologies can assist in investigating and preventing insurance claims fraud. By analyzing textual data from various sources, including claim descriptions, medical records, and external databases, these systems can identify suspicious patterns, uncover hidden connections, and provide valuable insights to fraud investigation teams.
Overall, AI and NLP solutions have the potential to revolutionize the insurance sector by improving efficiency, enhancing customer experience, mitigating risks, and ensuring compliance with regulations.