The Future of AI and Machine Learning in Fraud Detection
This transcript is edited from the TigerGraph Connections podcast published on September 12, 2022, with TigerGraph’s Sebastian Aldeco.Corey Tomlinson: Tumultuous times lead inevitably and unfortunately to fraud, especially for large…
How Graph Helped Expose the Russian Laundromat Network
Money laundering, fraud, and corruption are everywhere. The criminals behind it all have developed multilayered, intricate ruses to carry out their crimes, some of which are so complex that law…
Combating the Global Economic Impact of Money Laundering Using Graph Technology
https://www.youtube.com/watch?v=EdPGhasVngAMoney laundering is an important concern for many companies, especially in financial services companies. Employees at these companies are required to undergo fundamental training on identifying signs of money laundering,…
Podcast: Fraud Detection at Financial Institutions – With Harry Powell and Martin Darling
This transcript is edited from the TigerGraph Connections podcast episode published on May 20, 2022, with Harry Powell, Head of Industry Solutions at TigerGraph, and Martin Darling, Vice President, EMEA,…
Swarm Learning and Graph Analytics Create Another Quantum Leap in Fraud Detection
Fraud is a serious concern for nearly everyone, especially businesses operating in financial services. At the end of 2021, the annual Nilson Report predicted that credit card fraud will cost…
Protecting Telco Customers from Identity Theft and Artificially High Phone Bills
TigerGraph is only the anti-fraud solution that is flexible enough to continuously fight the constantly evolving nature of fraud. Are telco fraudsters just like financial fraudsters? We have grown accustomed…
Knowledge Graph and NLP revolutionize the way AML looks at PEPs
This is an abbreviated version of a presentation by Maria Singson and Deepti Soni, Mastech Infotrellis during the Graph + AI Summit 2021 conference The elusive “entity” in today’s Entity…
