Research published in the International Journal of Information and Communication Technology suggests that machine learning tools might be used to detect and so combat financial fraud.

Combatting today’s rapidly evolving attacks requires real-time fraud detection systems capable of identifying complex patterns across millions of data points.

Machine learning plays a critical role in fraud detection by identifying patterns and anomalies in real-time. It analyzes large datasets to spot normal behavior and flag significant deviations ...

Machine learning techniques, such as those using XGBoost algorithms, have been effectively employed to detect and prevent technological fraud by recognizing patterns in large datasets and ...

For more information on this research see: Practical Guideline To Efficiently Detect Insurance Fraud In the Era of Machine Learning: a Household Insurance Case. Journal of Risk & Insurance, 2023.

Here is how insurance companies are using ML to improve their insurance processes and flag insurance fraud before it affects their bottom lines.

A large part of official documentation comes via signatures, a historically popular method of fraud. Like fraud, machine learning compares signed documents to reference signatures.

Research data and fraud prevention business Rep Data has launched a machine learning-led anti-survey fraud tool.

Machine learning plays a critical role in fraud detection by identifying patterns and anomalies in real-time. It analyzes large datasets to spot normal behavior and flag significant deviations ...