In the long contest between those who guard financial systems and those who exploit them, each new defense has historically invited a new evasion — a cycle that exposes the limits of tools that only learn from the past. Researchers have now proposed a framework called GT-ACGL that reframes fraud detection not as pattern recognition but as strategic anticipation, modeling the relationship between defender and fraudster as a game between two reasoning players. Tested on benchmark transaction data, the system improved detection accuracy by 11 percentage points over leading alternatives, even unde