Fraud Detection Archives

Real-time Blockchain Fraud Detection

The Problem Real-time linking of transactions, accounts, wallets, and blocks within and across blockchains is not possible with current solutions. Instead, the user must either rely on batch processing, which means results are out of date, or perform recursive lookups across table joins, which means unacceptable latency. The Solution Graph data structures are ideal for modeling the relationships described in blockchain events. Flows of cryptocurrency between accounts and wallets are ideal...

Authentication Fraud

by thatDot | Use Cases

The Problem Metered attacks that generate low volume log-in attempts, from diverse IPs and across extended time frames, are designed to avoid the "3 strikes in 24 hours" business rules in authentication applications and the more complex analysis of log analytics / SIEM platforms. Batch solutions by definition cannot react until after a compromise has occurred while all real-time solutions impose time windows -- any data falling outside these rolling windows, no matter how important, is simply...

Financial Fraud Detection

by thatDot | Use Cases

The Problem Financial fraud detection requires monitoring billions of transactions, devices and users in real-time for suspect behaviors without false positives that alienate customers when service is denied in the middle of a foreign vacation or late night business event. The Solution What is needed is a system that do four things: detect complex patterns of behavior combine multiple sources and scale up to millions of events/sec take the appropriate, user-specified action when patterns are...