Machine learning is being widely adapted in industrial applications owing to the capabilities of commercially available hardware and rapidly advancing research. Volkswagen Financial Services (VWFS), as a market leader in vehicle leasing services, aims to leverage existing proprietary data and the latest research to enhance existing and derive new business processes. The collaboration between Information Systems and Machine Learning Lab (ISMLL) and VWFS serves to realize this goal. In this paper, we propose methods in the fields of recommender systems, object detection, and forecasting that enable data-driven decisions for the vehicle life-cycle at VWFS.
@article{arxiv.2202.04411,
title = {A.I. and Data-Driven Mobility at Volkswagen Financial Services AG},
author = {Shayan Jawed and Mofassir ul Islam Arif and Ahmed Rashed and Kiran Madhusudhanan and Shereen Elsayed and Mohsan Jameel and Alexei Volk and Andre Hintsches and Marlies Kornfeld and Katrin Lange and Lars Schmidt-Thieme},
journal= {arXiv preprint arXiv:2202.04411},
year = {2022}
}