Building a Custom Fraud Detection Dashboard
Creating a full web-app using Plotly Dash and TigerGraph Introduction In this blog, you’ll see some of the steps necessary to create a full fraud-detection web app connected to a…
How the World’s Largest Banks Use Advanced Graph Analytics to Fight Fraud
Originally featured on RTInsights.com Advanced graph analytics provides deeper insights, complementing BI, and helps organizations preempt and prevent potential fraud while protecting customers. Financial services organizations are both powerful and…
Machine Learning and Deep Link Graph Analytics: A Powerful Combination
Originally Posted on KDNuggets. Machine learning (ML) – an aspect of artificial intelligence (AI) that allows software to accurately identify patterns and predict outcomes – has become a hot industry…
Anti-Money Laundering (AML) Non-Compliance is Injurious to Your Business’ Health
On June 3 2018, the Commonwealth Bank of Australia was fined $700 million for AML non-compliance. Some of the problem areas at the bank included: Failure to properly monitor transactions for…
Finding Needles in a Haystack with Graph Databases and Machine Learning
You know a technology has reached a tipping point when your kids ask about it. This happened recently when my eighth grade daughter asked, “What is Machine Learning and why…
Blockchain, Bitcoin and The Art of Rolls Royce Repair
Two questions always come up when I tell people that I work on blockchain. The first question is “Where do I get started with blockchain in my organization?” and that’s…
Fighting Money Laundering with Real-Time Deep Link Analytics
Today, criminals are using extremely sophisticated, ever-adapting tactics to bypass traditional anti-fraud solutions for money laundering. Any organization facilitating financial transactions – including non-bank money service businesses such as digital/mobile…