How AI is Putting Fraudsters on Notice
“Whac-A-Mole” is typically a game played by children in an arcade. But individuals in fraud detection play a daily game of Whac-A-Mole: hammer down one threat of fraud, another fraud threat pops up almost instantly. Thankfully, artificial intelligence is the hammer making life a whole lot easier for executives tasked with keeping their company's finances secure. At its core, fraud detection involves identifying deceptive activities intended to provide a dishonest gain, often through theft or false representation.
For executives in fraud detection, the day-to-day involves analyzing suspicious transaction reports, assessing fraud risk dashboards, fine-tuning predictive algorithms, and occasionally enjoying a small victory dance when a big fraud attempt is thwarted. So how exactly is AI shaking up the game for fraud detection executives? Let's explore some real-world examples where technology is catching the cheats in their tracks.
Real-Life Examples of AI in Fraud Detection
AI isn't just theoretical magic; it's already on the front lines fighting fraud. Below are three standout examples of companies successfully deploying AI to catch fraudsters in their tracks.
1. Mastercard’s Real-Time AI-Powered Decision Intelligence
In May 2025, Mastercard’s flagship Decision Intelligence system proved its mettle—scanning nearly 160 billion transactions annually and assigning real-time risk scores in under 50 milliseconds. It now incorporates behavioral biometrics, analyzing how users type or swipe to detect imposters and flag first-party fraud like fraudulent chargebacks. This enhanced toolkit significantly reduces false positives while catching complex scams efficiently. Mastercard also rolled out Decision Intelligence Pro, which layers contextual behavioral insights over transaction patterns to improve accuracy without slowing customer experience.
2. PayPal’s AI-Powered Scam Detection for Friends & Family Payments
In July 2025, PayPal launched a dynamic scam detection feature specifically for its PayPal and Venmo Friends & Family payment flows. Using AI models that analyze billions of data points in real-time, the system proactively alerts users to potential scams—intervening before funds are sent. This innovation is designed to catch coercive or fake-payment scams often missed by traditional methods and exemplifies PayPal’s multi-pronged, adaptive fraud defense strategy.
3. Stripe Radar’s Expansion into ACH and SEPA Fraud Protection
Stripe’s Radar, already a leader in AI-driven card fraud prevention, was extended in early 2025 to cover ACH and SEPA payments using the same architecture. As a result, businesses using Radar saw average fraud reductions of 20% for ACH and 42% for SEPA. The system evaluates over a thousand transaction features in milliseconds and adapts behavior in real-time to evolving threats—bringing sophisticated fraud-detection capabilities to non-card payment types too.
Prompts for Fraud Detection
To help fraud detection executives tap into AI’s capabilities, here are five detailed prompts ready to integrate into your daily operations. Customize these prompts according to your organization's specific needs:
"You are an AI-powered financial security analyst. Review transaction logs from [insert date range here] for the account [insert account details]. Identify patterns indicative of fraudulent behavior and flag any unusual transactions with detailed reasoning."
"Act as an advanced fraud detection specialist. Examine the recent login activities for [insert user demographic, such as account managers or customer profiles] between [insert dates] and report any anomalies that could suggest unauthorized access attempts."
"You're a transaction fraud expert utilizing AI predictive analytics. Assess the following transactions [insert specific transactions or transaction types] processed within [insert time frame] and determine their likelihood of being fraudulent, providing a confidence score and rationale."
"Serve as an AI-driven risk assessment agent. Analyze patterns in refunds and chargebacks from [insert time period] for the region [insert region or segment] to identify any systematic attempts at refund fraud, highlighting critical cases that need immediate review."
"Assume the role of an AI fraud detection auditor. Review the behavioral data and transaction history of customers flagged by our preliminary monitoring system from [insert dates or time frame] and generate a concise report summarizing potential risks and recommending immediate actions."
AI isn’t just helping executives sleep better at night; it’s also ensuring fraudsters sleep a little less comfortably. As AI evolves, so do the defenses of businesses, creating an increasingly difficult environment for criminals to navigate. Executives leveraging AI-powered fraud detection not only protect their company's bottom line but also earn serious bragging rights at the next board meeting. It's safe to say, thanks to AI, fraud detection is becoming more precise, less stressful, and perhaps even a little enjoyable.
