Highly Accurate Document and Image Analysis Key to Decision
Shift Technology, a provider of AI-driven decision automation and optimization solutions for the global insurance industry, today announced the company recently delivered generative artificial intelligence (Gen AI) capabilities as part of their Shift Claims Fraud Detection and Shift Claims Intake deployments for Tokio Marine & Nichido Fire Insurance Co., Ltd. Shift’s Gen AI-powered visual intelligence capability uses Gen AI to improve the accuracy of image and document analysis, enabling precise identification of key information extracted from both structured and unstructured data. The use of visual intelligence contributes to the efficiency of insurance claims processing and further supports Tokio Marine’s initiatives to prevent fraudulent claims and streamline the claims process.
Claims professionals make key decisions throughout the claims process based on the documents and images provided by the policyholder and/or other involved parties. Reviewing, categorizing, and extracting information related to claims has long required significant time and effort. Further, insurers are now expected to confront the risks of new fraudulent claims that are difficult for the human eye to detect due to advances in technology. Gen AI has been demonstrated by Shift’s research team to excel at accurately categorizing the documents and images associated with claims and precisely extracting the right information required by claims professionals to make the best decisions possible. As such, it can be an effective approach to mitigating the fraud challenges faced by property and casualty insurance companies.
Shift has been providing Tokio Marine with solutions for fraud detection and claims processing optimization using approaches that leverage generative AI, machine learning, and IDP. These efforts support Tokio Marine’s purpose of “protecting customers and society in times of need.”
Shift Technology’s visual intelligence leveraging generative AI is expected by Tokio Marine to be an effective measure for preventing fraudulent claims and improving the overall insurance claims process.
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