Traditional fraud management relies on the detection of known fraud types by monitoring for known patterns of behaviour. Fraudsters have learnt the patterns and thresholds that are detected and have changed their approaches accordingly. This results in both nuanced changes to established patterns and entirely new frauds. Machine learning (ML)-based approaches enable communications service providers (CSPs) to dynamically establish new rules to combat known frauds as well as to discover unknown fraud types.

THIS REPORT:

• provides an update on the types of fraud and fraud management approaches that are needed to combat fraud within the telecoms sector
• looks at the different types of approaches to fraud management that are now possible with artificial intelligence (AI).