arXiv Machine Learning June 25, 2026 By Mohammadamin Dashti Moghaddam, Nick Sciarrilli

Multi-Stream Temporal Fusion for Financial Fraud Detection

Read the original on arXiv Machine Learning →

arXiv:2606. 25007v1 Announce Type: new Abstract: Financial fraud detection in digital banking requires reasoning over multiple heterogeneous event streams -- transactions, login sessions, risk signals -- that individually appear benign but collectively reveal fraudulent patterns.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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An AI Security Agent for Banking: Multi-Vector Fraud and AML Detection Across Retail and Corporate Accounts

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