Digital transactions have emerged as a dominant force in today’s global commerce sector, empowering businesses and financial ...

Insurance fraud detection using machine learning can help providers distinguish the fraudulent claims with higher efficiency and as a result, offer reduced premiums for the honest consumers.

Despite all of the safeguards and fraud detection systems in place, Capital One failed to monitor or detect the unauthorized activity.

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 ...

Findings on Machine Learning Reported by Investigators at Virginia Polytechnic Institute and State University (Virginia Tech) (Fraud Detection In Healthcare Claims Using Machine Learning: a ...

Combining the innate strengths of unsupervised and supervised machine learning to provide a Transaction Safety Rating is the second step in using machine learning to thwart bot-based fraud.

Artificial intelligence and machine learning (AI/ML) approaches can help by spotting patterns in previous fraud cases and using them to detect suspicious behavior by customers, employees or systems.

Rahul Chari, cofounder of PhonePe said that PhonePe trains their ML models mostly for the risk and fraud detection ...

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

They detect financial fraud transactions using machine-learning models trained on past examples of confirmed good and confirmed fraudulent behavior.