How Can Machine Learning Be Applied to Detect New, Evolving Forms of Front-Running?

Machine learning (ML) models can be trained on vast datasets of historical trading data to identify patterns indicative of known front-running. More importantly, unsupervised ML can detect anomalies ▴ new, subtle, or evolving trading patterns that deviate from normal market behavior ▴ which may represent novel forms of front-running or market manipulation that human analysts or rule-based systems might miss.