Online platforms have become integral to modern financial activities, which necessitates secure and seamless transactions, backed up by robust authentication mechanisms. Risk-based authentication offers a dynamic security approach, balancing user convenience with stringent fraud prevention.
The integration of cross-channel data and advanced technologies like machine learning (ML) and artificial intelligence (AI) is vital, as well as access and understanding of data. High-quality data is the cornerstone of effective fraud prevention and detection, which is why organisations must invest in robust data engineering practices to ensure collected data is accurate and well-labelled.
This investment enables the development of sophisticated models to better identify and prevent fraudulent activities. Prioritising data quality enhances fraud prevention strategies, protecting businesses and their customers from potential threats.
So how can organisations holistically address risk-based authentication in a dynamic world? This webinar report summarises the discussion of a Finextra webinar, hosted in association with Mastercard, and explores:
- Risk-based authentication in fraud prevention;
- Adapting fraud prevention to evolving threats;
- Advanced authentication strategies for corporate fraud prevention;
- Digital IDs, channels, and exclusion.