Incentive Program Fraud Is Evolving. Are Your Controls Keeping Up?

Fraud in incentive programs isn’t new, but where it’s showing up, and how it’s getting through, has changed.

Yesterday’s threats have evolved. Today, it’s duplicate submissions that slip past controls, dealer-driven claims that blur program intent, and unverifiable online purchases that still get paid. The result is the same: real program dollars tied to outcomes that don’t hold up under scrutiny.

The scale of the issue is getting harder to ignore:

• Rewards programs now see 6.19% attack rates, higher than cards, BNPL, and wallets (source)
• Rewards fraud drains $1–3B annually (source)
• Cashback fraud alone is about $120M/year, with ~4% of transactions showing red flags (source)
• Loyalty fraud is one of the fastest‑growing categories, with some studies citing ~89% YoY spikes (source)

For most organizations, the challenge starts where controls break down in practice. The same patterns show up across cashback and rebate programs, SPIFFs, MDF/Co-op, and B2B incentives.

Not edge cases. Repeatable failure points.

We’ve spoken to customers running these programs, and five pain points stand out:

1. Catching fraud after payout
2. Duplicate claims with modified dates
3. Online purchase verification
4. Manual review bottlenecks
5. Dealer and retailer submission fraud

Below, we break down each challenge and outline practical steps to strengthen your fraud defenses (without adding unnecessary friction for legitimate participants.)

Pain Points at a Glance

Pain Point #1: Catching Fraud After Payout

One of the most frustrating fraud scenarios is discovering fraudulent activity only after rewards have been paid out. Without real-time detection capabilities, organizations find themselves in a reactive position, unable to prevent losses before they occur.

How to fix it

Implement pre-approval fraud controls that analyze claims before payout. This includes:

• Serial number validation to verify product authenticity and prevent duplicate submissions
• Portfolio-wide intelligence (powered by shared watchlists and historical patterns) that helps identify bad actors who have attempted fraud in other programs
• Risk-based rules and flags that can automatically hold high-risk claims for review before processing payment
• Set up tiered audit processes where high-value claims receive 100 percent review, while lower-value claims use spot-checking to balance cost and protection.

Pain Point #2: Duplicate Claims With Modified Dates

Traditional duplicate detection misses one of the most common fraud tactics: submitting the same sale across multiple programs by simply changing the purchase date. Because the dates differ, these appear as separate transactions to basic duplicate controls.

How to fix it

Deploy advanced duplicate detection that looks beyond exact matches:

• Model and invoice combination tracking that identifies when the same product and invoice number appear with different key dates across programs
• Portfolio-wide duplicate checking that analyzes claims across your program portfolio, not just within individual programs
• Intelligent flagging that alerts reviewers when a claim matches previous submissions on all attributes except the date

Pain point #3: Difficulty Verifying Online Purchases

Validating online purchases from major retailers like Walmart, Amazon, and Canadian Tire presents unique difficulties. These retailers don't cooperate with verification requests, and fraudsters can easily create convincing fake invoices that replicate legitimate online order confirmations.

How to fix it

Use pattern analysis and practical verification steps when direct retailer verification isn't possible:

• Document consistency checks that surface anomalies (for example: missing or mismatched fields, unusual formatting, or repeated document patterns across submissions)
• Watchlist and consortium-informed intelligence that can flag known bad actors across your platform before they successfully claim

Consider requiring additional verification for online purchases, such as order confirmation emails or account screenshots, to add friction for fraudsters while remaining reasonable for legitimate customers.

Pain Point #4: Manual Review Bottlenecks

The manual effort required to review and validate suspicious claims creates significant operational bottlenecks. Without dedicated fraud review teams, organizations either accept questionable claims to avoid delays or create frustrating wait times for legitimate customers.

How to fix it

Automate routine fraud checks to free your team for complex cases:

• Automated rule-based screening that can streamline low-risk claims and routes higher-risk submissions for review based on predefined criteria
• Risk-based audit allocation where you audit 100 percent of high-value claims but only spot-check lower-value submissions
• Centralized fraud review teams with specialized training and tools, rather than distributing review across multiple staff members
• Clear escalation workflows that route flagged claims to the right reviewers quickly and track resolution times

The goal is to let technology handle the obvious cases (both clearly legitimate and clearly fraudulent) so human reviewers can focus on the nuanced situations that require judgment.

Pain Point #5: Dealer and Retailer Submission Fraud

Dealers or retailers may submit claims on behalf of customers, sometimes circumventing program intent or inflating claim volumes.

How to fix it

Implement controls specific to dealer and retailer behavior:

• Velocity checks that flag when a single dealer or email address submits claims at rates significantly above normal patterns
• Email domain validation that requires consumer programs to use consumer email addresses, not dealer or retailer domains
• Redemption method restrictions that prevent dealers from selecting physical cards sent to business addresses for consumer programs
• Baseline analysis that compares claim volume against expected activity based on purchase history or program enrollment
• POS data cross-referencing that validates dealer claims against actual sales data when available

For dealer programs specifically, consider implementing approval workflows for claims that exceed typical patterns, and maintain clear communication about program rules and acceptable claiming behavior.

Red Flag Checklist: Is Your Incentive Program Protected Against Fraud?

Use the questionnaire below to pressure-test your current controls:

• Are duplicate claims—especially those with modified dates or details—automatically flagged across all programs?
• Does your system validate serial numbers, invoices, and purchase documentation before payout?
• Can you detect patterns of suspicious activity, such as repeated claims from the same email, IP address, or dealer?
• Are online purchases verified with layered checks, even when retailer cooperation isn’t possible?
• Is there a watchlist or consortium intelligence that identifies known bad actors across your portfolio?
• Are high-value or high-risk claims automatically routed for additional review, while low-risk claims are fast-tracked?
• Do you have velocity checks and domain validation to spot abnormal dealer or retailer behavior?
• Are manual reviews reserved for exceptions, not the rule—reducing bottlenecks for legitimate participants?
• Can you easily audit and adjust fraud controls as new threats emerge?

If you answered “no” or “not sure” to two or more of these, you likely have material fraud exposure. Not because of a single gap, but because your controls aren’t aligned to how fraud actually occurs across programs.

You need to:

• Move controls pre-payout so high-risk claims never get processed in the first place
• Detect duplicates across programs, not just within them
• Tier decisions by risk, so your team isn’t manually reviewing what automation can handle
• Apply dealer-specific controls, where behavior—not just documentation—drives risk

As a starting point, pressure-test your current setup over the next 30 days:

• Measure duplicate rates, late-stage reversals, and online order anomalies
• Identify where claims are being approved without sufficient validation
• Track how much review effort is spent on low-risk vs. high-risk claims
• Map where fraud is being caught: before payout, or after

Most teams already have some controls in place. The difference is whether those controls are working at the point where they actually prevent loss, or just helping you explain it after the fact.

At 360insights, this is exactly where our Incentives Suite and fraud controls go to work: aligning pre‑payout checks, duplicate detection, dealer oversight, and audit‑ready governance across rebates, SPIFFs, rewards, and MDF/Co‑op in one environment. We take care of the fraud protection. You grow programs confidently, without funding fraud you can’t see.