Tao Zhang is a Director at Treliant. He has over 20 years of experience in Anti-Money Laundering (AML) transaction monitoring compliance and other monitoring compliance programs. Tao has played key roles in projects in more than 10 major financial institutions in all key areas of their AML transaction monitoring compliance program including AML data models (data mapping and extract, transform and load controls), coverage/risk assessments, AML detection models (selection, development, configuration, testing, assessment, validation, tuning, optimization, and audit), and AML due diligence models (validation, optimization). He is expert in all major commercial tools for AML transaction monitoring systems including Oracle/Mantas, Actimize, SAS, and Prime. He specializes in providing in-house tools for AML model detection, validation, tuning, and optimization in one automated process by generating detection alerts, validation alerts, tuning alerts, and optimization alerts for effective and efficient risk management that covers all major stages of the lifecycle of AML model risk.
His experience also includes research and development of the original algorithms and models for AML transaction monitoring at Mantas, including the first U.S. patent for Mantas. He did proof of concept to attract Mantas’ first client, Citibank. He developed and delivered a USPS customer satisfaction monitoring system/tool at IBM. He developed and managed a transaction monitoring system to track data quality, fraud, and other issues at Visa.
His extensive experience in AML transaction monitoring compliance at multiple major financial institutions includes a critical project of the Oracle/Mantas implementation including data model, detection model, and due diligence model in a few months under the regulatory scrutiny of enforcement actions. He also conducted a validation that resolved a dispute between a bank and a major consulting company regarding the AML model validations conducted by the consulting firm under regulatory enforcement actions. In addition, he developed and delivered an in-house AML transaction monitoring system to replace the commercial AML monitoring system at a major bank.
He holds a PhD in Theoretical Particle Physics from York University. He has published numerous papers in physics and data mining, and he has also had several U.S. patents in database applications, data mining, and AML transaction monitoring. He was invited panel speaker at ACAMS 7th Annual AML Risk Management Conference on the topic of “A Match Made in Risk Management Heaven: AML Compliance and Artificial Intelligence.”