I am attending the 2017 IEEE International Conference on Big Data in Boston, Massachusetts, to present our paper
Predicting over-indebtedness on batch and streaming data.
Abstract: Detecting over-indebtedness, the difficulties meeting household payment commitments, poses multiple Big Data challenges for banking institutions. We present a novel data-driven framework for predicting over-indebtedness on real-world data. A warning mechanism that generates predictions 6 months ahead, improving the chances of financial recovery. This framework is based on the combination of feature selection and supervised learning techniques, and uses data balancing for fine-tuning the predictive models.