The case study describes how D&G enhanced pricing performance by adopting advanced analytics and machine learning to better support its customer‑centric mission. Traditionally, the insurer priced appliance and white goods warranties using limited product attributes such as make, model, and age, which had worked but lacked personalization. Recognizing the opportunity to better understand customers and improve efficiency, D&G began exploring more sophisticated pricing models in 2016. By leveraging analytics and machine learning with Earnix, D&G improved pricing speed, flexibility, and insight, enabling more personalized offers, stronger customer alignment, and improved pricing success in a competitive insurance market.

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