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A new family of Android click-fraud trojans leverages TensorFlow machine learning models to automatically detect and interact with specific advertisement elements. [...]
XML-Based Messaging Tech Extends Fraud Detection Into Wider Bank Use CasesACI's signals network intelligence harnesses neural networks and federated machine learning to spot fraud in real time without banks sharing data. Beyond fraud detection, its insights can drive business growth from other business units, and ACI aims to accelerate adoption by making it open source.
Experts Weigh the Advantages and Risks of Generative Adversarial NetworksWith traditional rule-based fraud detection systems and even conventional machine learning models struggling to identify these highly deceptive fraud patterns, financial institutions are exploring generative adversarial networks to enhance fraud detection.
Javelin's Jennifer Pitt on AI-Powered Detection of Authorized Payment FraudMachine learning helps banks detect APP fraud by analyzing large transaction datasets faster. These AI models operate in near real-time and can distinguish legitimate transactions from fraudulent ones by spotting anomalies, said Jennifer Pitt, senior analyst at Javelin Strategy & Research.
Featurespace's AI Expertise Will Enhance Visa's Fraud, Risk and Payments TechnologyVisa has signed a definitive agreement to acquire AI-driven fraud prevention leader Featurespace. This acquisition will reinforce Visa's fraud detection capabilities, integrating advanced machine learning technology to strengthen financial crime prevention and protect global transactions.
As cybercriminals tap the power of machine learning and generative AI to outwit fraud-detection systems, online fraud-prevention technologies must evolve accordingly.
Financial services firms need to learn how — and when — to put machine learning to use.
As the use of AI- and ML-driven decision-making draws transparency concerns, the need increases for explainability especially when machine learning models appear in high-risk environments.