This blog post uses Neo4j and GRANDstack to build a graph and timeline visualization app that drives fraud investigations. It focuses on fraud in Wikipedia articles about the 2020 U.S. election presidential candidates, exploring why an anomaly detection platform featuring dedicated timeline analysis is an effective choice. The author loads Wikipedia data into Neo4j using the MediaWiki API, then visualizes it with ReGraph and KronoGraph to detect potentially fraudulent behaviors. The app features a network view of connections between editors and pages, as well as two fully-interactive time-based components: the ReGraph time bar at the bottom of the screen and KronoGraph timelines to the right of the network. These tools allow for the exploration of editing patterns, recognition of outliers, and spotting periods of intense activity, ultimately driving fraud investigations with smarter analytics.