The financial services sector is in a constant state of evolution, and so too are the challenges it faces, particularly in the realm of financial crime. This mounting issue has become a significant concern for institutions, customers and regulators alike. The key to addressing this lies in our approach to data - its quality, management, and applications.
Harnessing the power of synthetic data and AI tools has become a pivotal factor in business transformation, particularly in addressing the issue of financial crime. The ability to streamline operations and enhance efficiency is a major challenge businesses face, but the introduction of synthetic data offers promising solutions.
Synthetic data provides a comprehensive view of all types of crime, a feature that is crucial for global banks often grappling with segmented fraud activity. This broader perspective enhances the institutions’ capability to effectively fight financial crime.
This report summarises the discussion had during a Finextra webinar, hosted in association with Red Hat, and explores:
- The role of synthetic data in combatting financial crime
- Implications of new regulation
- How synthetic data enhances crime detection
- A practical apprach for managing fraud risk