Our Ideas

User Behaviour Analytics in fraud detection: bridging the gap between payments and cybersecurity

Originally developed for an audience in the Payments Village at DEFCON, this article by Fortify founder Karthik Tadinada explores how User and Entity Behaviour Analytics (UEBA) can identify anomalies in user and device behaviour, providing critical insights for fraud prevention. By analysing behavioural patterns, UEBA helps detect suspicious activities in real-time. This approach is particularly useful in payment fraud detection - and also in cybersecurity - where human-driven events trigger responses in decision systems, offering a powerful tool for mitigating unwanted behaviour.

Harnessing AI and machine learning for advanced fraud detection

The fraud detection landscape is shifting dramatically. Traditional methods of prevention struggle to keep pace with increasingly sophisticated threats. This article underscores the necessity of integrating AI and ML into fraud prevention strategies. These technologies can analyse vast datasets in real-time, stopping fraud in its tracks. Navigating this new era of fraud prevention demands a strategic investment in AI and in human expertise to stay ahead of emerging threats and protect financial ecosystems effectively.

Strategies for combatting cryptocurrency fraud today

This article explores the unique challenges posed by digital currencies. To effectively manage these issues, banks must ensure regulatory compliance, enhance due diligence, and make use of advanced technologies for fraud detection. Strengthening cybersecurity defences, collaborating with other banks and providing comprehensive employee training are also essential. By adopting a proactive, informed approach, banks can harness the benefits of digital currencies while effectively mitigating the risks of crypto-related fraud.

4 ways to enhance your fraud and risk systems

This article shares tips on how to strengthen your fraud defences. First, prioritise high-quality, diverse data inputs that can detect anomalies quickly. Then, equip teams with advanced tools (and the skills to use them), such as AI and machine learning. Stay agile, continuously monitor, test, and adjust systems. Finally, use DORA metrics to evaluate the performance, of your models.

How big data and analytics can strengthen your fraud prevention

As our lives increasingly unfold online and artificial intelligence advances, the complexities of fraud and cyber threats grow. This article explores how data analytics and machine learning are transforming fraud detection. It underscores the crucial role of pattern recognition, real-time monitoring, and predictive modelling in identifying and mitigating fraud risks. By focusing on data and investing in innovative technologies, financial institutions can successfully navigate the evolving landscape of threats.

Need expert advice?

Get in touch