How to Use Algorithms to Identify Suspicious Activity in Real-Time
The growth of fraudulent activity poses a significant threat to businesses in today's increasingly digital environment. The techniques fraudsters use are continuously evolving-making it difficult for traditional rule-based systems to stay up, as the estimated corporate revenue lost to fraud stands at $4.7 trillion globally every year. Employing increasingly advanced and dynamic fraud detection techniques have become essential. Machine learning is the most promising technology tool to combat financial fraud.