Lenders tap alternative data as next frontier in credit fraud fight

Fintechs, credit platforms analyse digital footprint, metadata, behaviour to detect fraud and underwrite new-to-credit users

Risk assessment platforms are increasingly using diverse data sources to help lenders identify groups attempting to access credit from regulated entities and to improve the process of evaluating new-to-credit (NTC) users.

 

Companies are training models on various forms of alternative data — such as location details, third-party app usage, SMS data, payment transaction behaviour, and metadata — to enhance underwriting for NTC customers.

 

Fraud syndicate detection often stems from analysing alternative data patterns, such as multiple government IDs linked to a single mobile number, particularly in high-risk regions with a history of fraudulent activity.

 

“What we look for are aggregated