AXA, the large global insurance company, has used machine learning in a POC to optimize pricing by predicting “large-loss” traffic accidents with 78% accuracy.
AXA is still at the early stages with this approach — architecting neural nets to make them transparent and easy to debug will take further development — but it’s a great demonstration of the promise of leveraging these breakthroughs.
In contrast, after developing an experimental deep learning (neural-network) model using TensorFlow via Cloud Machine Learning Engine, the team achieved 78% accuracy in its predictions. This improvement could give AXA a significant advantage for optimizing insurance cost and pricing, in addition to the possibility of creating new insurance services such as real-time pricing at point of sale. AXA is still at the early stages with this approach — architecting neural nets to make them transparent and easy to debug will take further development — but it’s a great demonstration of the promise of leveraging these breakthroughs.
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