Ghost students are detected by looking for patterns across the enrollment lifecycle, shared contact information, simultaneous enrollment at multiple institutions, mismatched application data, and minimal engagement after enrollment. Many of these signals only become visible when records are compared across institutions, which is why network-level intelligence has emerged as a core detection layer alongside on-campus identity verification.
