Recent studies from leading financial institutions show that financial fraud continues to rise at alarming rates. According to Experian, credit and debit card fraud has risen over 60% in the first half of 2019. Although Millennials are highly targeted (an 80% chance of being a target of fraud), no one is immune from criminal activity.

Home grown fraud rules, based on in-house subject matter expertise and observations, are commonly used to counter fraud attacks as well as other financial crimes, such as Anti-Money Laundering.

Altair offers an industry leading approach to augment/adjust these rules based on actual analytical models. The benefit realized is that fraud analysts can update rules without needing to turn to highly utilized resources such as data scientists.

Learn how users of Altair predictive analytics enables fraud analysts and others to:

• Visualize existing rules, optimize them, and how to create new rules
• Use machine learning to improve the accuracy of identifying fraudulent credit applications
• Share insight across the organization using easy to understand predictive models such as decision trees