In a galaxy far, far away, financial fraud poses a growing threat to the stability of interplanetary systems. This session explores the application of machine learning and graph technology to uncover fraud cases within the Galactic Empire. The resistance is fighting back and employing a new state-of-the-art 23ai database from Oracle.

An ML model that identifies suspicions by constructing a multidimensional graph with nodes representing key figures such as Jedi, Sith, smugglers, and bounty hunters and edges denoting transactional relationships.

The study incorporates advanced algorithms like decision trees, random forests, and neural networks (NNs) to detect anomalies that could indicate fraudulent activity. The results showcase how these technologies can efficiently pinpoint deceptive actions hidden within complex interstellar dealings, offering a powerful tool for ensuring financial transparency across the galaxy.

Additional Notes:
The findings are illustrated with fictional case studies involving notorious Star Wars characters, demonstrating how ML and graph-based analytics can uphold justice in the face of galactic fraud and allow the resistance to beat the dark side. The demo will enable people to walk away with new skills to apply to there business.

Technology: Oracle 23ai, Graph, Data Science