Fraud and revenue assurance is a major issue within the telecoms industry, directly impacting revenues. Currently, most network operators utilise fraud mitigation tools which use rules based logic to identify fraudulent behaviour. However, supervised machine learning is now being used to develop algorithms that can automatically identify activity as fraudulent or non-fraudulent. Machine learning may also offer the potential to spot early trending anomalies associated with criminal behaviour.