Publication Type
Conference Proceeding
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Supervisor
Publication Year
2025-07-10
Journal
Book
Proceedings of the 13th IMA International Conference on Modelling in Industrial Maintenance and Reliability
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Abstract
The Right to Repair legislation requires original equipment manufacturers to make repairs more accessible. While this legislation helps consumers, manufacturers must consider the additional costs of returning and repairing products. Our model predicts the cost of returning a product, allowing manufacturers to determine optimal warranty pricing before the product is sold. The model is developed using actuarial best practices, combining return costs with claims frequency, and trained using gradient-boosting predictive models. We validate our approach on a dataset of 25,000 returns from an automotive supplier over five years. By predicting return costs, our model supports optimal warranty pricing.
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Keywords
Machine Learning, Predictive Model, Product Return, Warranty