Anomaly Detection – Using unsupervised Machine Learning for detecting anomalies in customer base

Many companies have problems to detect anomalies (outliers) in their customer base in an automated way. The reasons for this are manifold, such as data availability or rule-based approaches that cannot cover the full data potential. Unsupervised machine learning models based on a fundamental holistic customer view can help to identify relevant outliers and highlight corresponding outlier reasons.