The main factors include a surge in digital transactions, the shift to remote work, and a decrease in control measures.
Globally, the financial toll of fraud surpasses $1 trillion annually, with U.S. financial services incurring an additional expense of $4.23 for each dollar lost to fraud.
The market is expected to grow from $43.97 billion in 2023 to $182.66 billion by 2030, achieving a compound annual growth rate (CAGR) of 22.6%.
AI and machine learning can analyze large data sets to detect patterns and anomalies indicative of fraudulent activities, thereby improving accuracy and efficiency in fraud detection.
Real-time fraud detection is crucial in environments with rapid transactions, as it allows for immediate action to prevent potential losses.
FaaS involves criminals offering fraud infrastructure as a service, making it easier for non-technical fraudsters to carry out attacks.(link to article 2)