The purpose-built AI platform can detect complex subrogation recovery opportunities that can slip through a regular triaging process.
Any claim dataset. Any level of complexity. Any stage of transformation.
To succeed at an end-to-end digital claims closure without escalating costs, insurance companies need a strong functional system that allows seamless data ingestion throughout the claims lifecycle to detect recovery potential and potential subrogation. Our AI is trained to extract relevant facts, apply applicable state laws, and then leverage a deep learning model to predict damage severity and subrogation.
[layerslider_vc id=”3″]
Digital Subrogation Prediction in Three Effortless Steps
[layerslider_vc id=”4″]
Our advanced, multi-pronged deep learning approach uses image recognition in incidents, pattern detections in structured and unstructured data and uses supervised and unsupervised learning for initial training and then reinforcement learning for continuous training for enhanced predictions over time.
