Fraud never stands still. It adapts, accelerates, and embeds itself in everyday transactions, often hiding in plain sight. Each month, Rippleshot's proprietary fraud data – sourced from over 5,000 financial institutions and 50 million daily card transactions – offers a uniquely predictive view into how fraud is evolving. This blog draws from our newly released May 2025 Fraud Intelligence Report, containing insights not available anywhere else in the market.

This post breaks down the key findings, explores the underlying behaviors driving them, and offers actionable recommendations to help financial institutions stay ahead of sophisticated threats.

Key Finding #1: Fraud Is Shadowing Seasonal and Economic Spend Trends

Notable Categories: Home Supply Warehouses (MCC 5200), Bicycle Shops (MCC 5940)

In May’s report, Rippleshot detected a synchronized rise in both legitimate spend and fraud in sectors traditionally impacted by springtime consumer behavior. Home improvement and recreational activity spending surged due to warmer weather and tax refund season. Fraudsters took notice.

Fraud at Home Supply Warehouses jumped 23.63%, double the rate of legitimate spend growth. These fraud patterns suggest attackers are embedding activity in seasonal peaks, when transaction volume can obscure anomalies.

What’s Driving It:

The high-ticket, easily returnable nature of products like power tools and appliances, combined with frictionless online/in-store pickup options, create fertile ground for fraud.

What It Means for Financial Institutions:

Card issuers should consider seasonally adjusted risk models. Merchant-level monitoring tied to consumer cycles is essential for identifying fraud spikes that align with legitimate trends.

Key Finding #2: Fraud Persists in High-Risk MCCs – Even as Dollars Decline

Notable Categories: Electronics Sales (MCC 5732), Discount Stores (MCC 5310)

Even as total fraud dollars declined in some traditionally targeted verticals, fraud rates remain alarmingly high – 77.82 bps in electronics, 37.93 bps in discount stores.

Why It Matters:

This points to concentrated, persistent fraud in categories with high resale value and minimal friction. Attackers are not necessarily scaling their volume, but they’re optimizing for impact. These MCCs remain prime targets for synthetic identity abuse, card testing, and organized ring activity.

Recommended Action:

Continue targeted rule enforcement even when fraud volumes drop. These are high-likelihood attack vectors that require persistent attention.

Key Finding #3: High-Growth Fraud in Low-Visibility Categories

Notable Category: Quasi Cash (MCC 6051)

In one of the sharpest contrasts seen this month, fraud in Quasi Cash categories increased by 38.26%, while legitimate spend dropped by 5.37%.

Why the Spike?

This pattern signals sophisticated abuse in channels often used for laundering or synthetic fraud:

• Cryptocurrency purchases
• Wallet funding services
• Gift card abuse

With a fraud rate of 9.91 bps, Quasi Cash is becoming a magnet for highly targeted attacks, likely due to its relatively opaque transaction nature and fewer guardrails.

Strategic Insight:

This isn’t opportunistic fraud; it’s calculated. Banks and credit unions should implement high-sensitivity monitoring and consider pre-emptive rule generation through platforms like Rippleshot Rules Assist to proactively block emerging fraud types in these channels.

Strategic Insights for Fraud Teams

1. Don't Just Follow the Money – Follow the Anomalies

Fraud patterns are no longer tied solely to dollar volume. Emerging trends show targeted abuse in low-spend categories where fraud spikes are harder to detect.

2. Lean into Predictive Intelligence

Tools like Rippleshot’s Rules Assist help teams get ahead with AI-powered merchant-level decision rules. Case studies show a 7x ROI, with false positive rates 46% lower than industry average.

3. Monitor Spend-Fraud Divergence Closely

Rippleshot’s Relative Fraud Growth Index identifies where fraud is outpacing spend. Categories with an index >1 deserve elevated scrutiny – especially during seasonal peaks or economic stimulus events.

4. Pair Card and Merchant Intelligence

Use solutions like Sonar to align merchant-level risk with at-risk card signals. Financial institutions using Sonar report up to 10x more compromised cards detected than traditional network alerts. Pair merchant risk with at-risk card signals to optimize which cards to take action on – cutting down account holder impact and false positives.

Conclusion

Fraudsters are getting smarter. Rippleshot's data gives you insight into their behavior, and tools to mitigate account holder impact. Their ability to blend into consumer behavior and exploit systemic gaps requires institutions to move from reactionary defense to proactive prediction.

With consortium-level visibility and tools that marry card, merchant, and behavior analytics, fraud professionals can outpace the evolving threat landscape.

Now is the time to transition from detecting fraud to anticipating it.

For a full briefing or to learn more about how Rippleshot can help your institution stay ahead of fraud, visit www.rippleshot.com.