TigerGraph > Case Studies > Improving Anti-Money Laundering with TigerGraph

Improving Anti-Money Laundering with TigerGraph

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 Improving Anti-Money Laundering with TigerGraph - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Machine Learning
  • Cybersecurity & Privacy - Identity & Authentication Management
Applicable Industries
  • Finance & Insurance
Use Cases
  • Fraud Detection
  • System Integration
The Challenge
The financial institution was looking to improve its networking and link analysis capability for anti-money laundering.
The Customer
About The Customer
The company is a major financial institution in the United States, providing banking, investment, mortgage, trust, and payment services products.
The Solution
TigerGraph provided the financial institution with the ability to perform in-depth analysis and see connected data in context. It also offered scalability and extensibility through machine learning.
Quantitative Benefit
  • The company achieved increased effectiveness, efficiency, and productivity in its anti-money laundering efforts.

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