Page 101 - Cyber Defense eMagazine August 2024

1. AI Fraud Detection in Finance

The banking and finance industry was an early adopter of AI-powered fraud detection, and it’s easy to
see why. Machine learning models can spot stolen credit cards quickly and accurately by detecting
purchase behavior that doesn’t match a customer’s previous buying history.

Banks monitored transactions for unusual activity long before the advent of AI. However, machine
learning can perform this work faster and more reliably than humans. As a result, fraud detection has
emerged as the number one AI use case among financial institutions.

2. AI Fraud Detection in E-Commerce

E-commerce is another sector that can gain a lot from AI fraud detection. As online sales grow, these
stores and their customers’ accounts become bigger targets for cybercriminals. Consequently, they must
find breaches quickly, but doing so amid such high transaction volumes can be difficult. Automation
through AI is the answer.

Online stores have extensive user data, as 65% of American shoppers prefer self-service through
chatbots and other AI tools. As a result, e-commerce companies already have enough information on
each user to recognize abnormal behavior. Connecting these AI solutions to fraud detection algorithms
makes security faster and more accurate than manual alternatives.

3. AI Fraud Detection in Government

AI-powered fraud detection has also seen rising use among government organizations. The same
algorithms that let banks catch breached accounts enable government agencies to detect fraudulent tax
and benefit claims.

The U.S. Treasury recovered more than $375 million in 2023 alone after using AI fraud detection tools.
Part of this success stems from AI’s accuracy in identifying suspicious trends, but the automation aspect
plays a part, too. Uncovering potential fraud with technology takes much less time than the conventional
approach, so government agencies can manage more cases with fewer resources.

4. Phishing Detection

Fraudulent transactions may be the most obvious targets for AI fraud detection, but they’re not the only
ones. This technology is also useful in more cybersecurity-specific use cases. Phishing prevention is an
excellent example.

Phishing is by far the most reported type of cybercrime, and this popularity is largely due to its efficacy.
It’s hard for users to spot every phishing attempt. AI can help by analyzing real-life phishing examples to
learn common markers of these fraudulent messages. It can then flag messages as possible phishing to
make people more aware of these risks, preventing costly errors.

Cyber Defense eMagazine – August 2024 Edition 101
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