Galileo Warns Static Rules Fail Modern Fraud Detection

According to PYMNTS, Maxim Spivakovsky, senior director of global payments risk management at Galileo, said modern fraud has outgrown static rules and that many firms still struggle to use data with precision. PYMNTS reports Spivakovsky as saying, "Data is one of the biggest plays right now in the market," and that "the lagging organizations treat the data as a storage problem while the leading organizations actually treat it as a decisioning system." The article summarizes his argument that decision quality is the central metric separating leaders from laggards.

Industry-pattern observations: Payments and fraud teams face two linked engineering challenges when moving from static rules to adaptive decisioning. First, real-time ingestion and feature computation at scale require low-latency data pipelines and streaming feature stores. Second, establishing closed-loop feedback for model evaluation and retraining demands consistent labels and infrastructure for online experimentation. These patterns recur across vendors and platforms adopting real-time decisioning architectures.

Industry-pattern observations: The PYMNTS account frames AI-driven, adaptive controls as shifting the emphasis from individual model performance to operational decision quality. In comparable transitions, firms that unify telemetry across products and close feedback loops typically gain faster detection lift than those that only adopt point-solution models. This advantage often arises from richer contextual signals and faster model iteration, not solely from headline model changes.

Editorial analysis: Observers should monitor three operational indicators across providers and merchants: the adoption of streaming feature stores, the prevalence of automated feedback labeling for fraud outcomes, and investments in latency-reducing infrastructure for real-time scoring. PYMNTS did not publish a technical whitepaper with benchmarks in this piece, and Spivakovsky provides qualitative assessment through the interview format.