Why chargebacks are just one piece of the fraud puzzle

At a glance:

• Chargeback rate alone captures only a narrow slice of fraud losses, hiding bigger issues affecting revenue, operations, and brand trust.
• Account takeovers, false positives, operational drag, and brand experience risk are growing across ecommerce, airlines, iGaming, banking, and money movement platforms.
• IPQS VP of Fraud Strategy Alexander Hall urges teams to track metrics like approval rate for good customers, false positive rate, manual review rate, and account takeover incidents alongside chargebacks.

The chargeback trap most fraud teams fall into

For most fraud teams, performance still comes down to a single number: chargeback rate. It is visible, painful, and tied directly to card network thresholds, so it naturally becomes the north star for every fraud program. But as Alexander Hall, the newly appointed VP of Fraud Strategy at IPQS, explained in a recent conversation with Jordan Harris of The Fraud Boxer, that single metric is a dangerously incomplete picture.

Chargebacks capture only a narrow slice of fraud losses. When teams focus on them alone, they can hide bigger issues that affect growth, customer experience, and long-term profitability. Cases that eat into margins just as much as disputes often go untagged as fraud in internal reporting, which means they never inform future risk decisions. Hall's argument is that organizations need to broaden how they measure fraud — not because chargebacks are irrelevant, but because the cost of ignoring everything else has become too large to absorb.

Hidden fraud impacts that rarely show up in metrics

One of the fastest-growing problems Hall highlights is account takeover (ATO). Ecommerce and airlines are experiencing a troubling rise in successful ATOs, and the downstream effects are severe. A successful ATO quickly undoes the hard work teams put into creating seamless user experiences. It drives customer churn, increases acquisition costs through negative word of mouth, and enables off-platform identity theft through stolen personally identifiable information (PII). Victims also face direct losses, such as reimbursing stolen stored value and loyalty points.

The pattern is not limited to travel and retail. iGaming platforms are seeing fraudulent withdrawals after account changes. Banking is facing a surge in synthetic identity fraud. Money movement platforms are dealing with identity theft used to create and operate fraudulent businesses. In every case, the losses are real, but they rarely register as a chargeback, so traditional metrics miss them entirely.

The revenue you never earn: false positives and friction

The other side of the fraud equation is the revenue organizations simply never capture. When rules or tools are too strict, good customers are declined or forced into slow manual reviews. False positives are one of the largest and least visible costs of fraud prevention. A legitimate customer who gets blocked because their IP address, device, or email "looks risky" may abandon the purchase and never return.

From IPQS' vantage point, this is where accurate risk scoring and tuning matter as much as catching fraud itself. Every suspicious order that goes to manual review adds labor cost, slows fulfillment, and creates friction for customers waiting on decisions. Fraud-related tickets also pile up in support queues, from refund requests and account lockouts to disputes over promotional abuse. Over time, the operational drag of managing fraud can rival direct loss, especially for high-volume merchants and platforms.

Brand and customer experience risk

Fraud is ultimately a trust problem. When accounts are taken over or fake accounts abuse a platform, legitimate users start to question whether their data and money are safe. IPQS frequently works with companies where fraud has become a brand issue, not just a risk issue: users lose confidence after seeing spam, scams, or repeated login problems, and organic growth slows because word of mouth suffers.

Hall frames this as a critical reason teams should look beyond chargebacks. A mature fraud program treats chargebacks as one outcome among many, not the whole picture. The strongest programs are not just "stopping fraud" but actively protecting customer experience, enabling marketing to scale safely, and giving leadership confidence that risk controls support long-term growth rather than restrict it.

Key metrics to track alongside chargebacks

IPQS outlines several metrics that, tracked side by side with chargebacks, give a much clearer view of whether fraud controls are truly supporting growth:

• Approval rate for good customers
• False positive rate or "good customer decline" rate
• Manual review rate and average decision time
• Volume and value of fraud-related refunds or credits
• Abuse rates for promotions, referrals, and loyalty programs
• Account takeover incidents and new account abuse volume

These metrics force teams to confront questions they might otherwise avoid: Where are we writing off loss that is not labeled as fraud today? How many legitimate orders are delayed or declined by current controls? Which marketing or growth programs see the highest rate of abuse? How often do fraud cases create support tickets or manual work for other teams? Do we have a shared view of fraud impact across risk, product, finance, and marketing?

How IPQS approaches fraud measurement

As a fraud and risk data provider, IPQS is designed to plug visibility gaps rather than just block obvious bad payments. Its scoring looks at the user and their behavior across signals like IP reputation, device intelligence, email history, and past abuse patterns, not just the payment details in front of you. The goal is to help teams:

• Catch more fraud before it becomes a chargeback
• Reduce friction and false positives for legitimate customers
• Identify patterns of abuse in accounts, promotions, and traffic sources
• Feed more accurate data back into internal reporting and decisioning

When risk scores and signals align with a company's own outcomes data, fraud metrics evolve from "chargebacks this month" to "total impact on revenue, costs, and growth." Hall's message is that aligning on these questions helps teams move from reactive dispute handling to proactive fraud strategy.

What to watch next

The conversation around fraud measurement is shifting from a compliance checkbox to a growth conversation. As synthetic identity fraud, ATOs, and promotional abuse continue to rise across verticals, the teams that broaden their metrics first will be better positioned to scale safely. IPQS offers a free trial for organizations looking to test whether their current fraud controls are capturing the full picture.

Tags: fraud prevention, chargebacks, account takeover, false positives, IPQS, fraud metrics

FAQ: [ { "q": "Why are chargebacks considered an incomplete fraud metric?", "a": "Chargebacks capture only a narrow slice of fraud losses — cases that result in a formal dispute with the card network. Many fraud-related losses, such as account takeovers, synthetic identity fraud, promotional abuse, and false positives, never appear as chargebacks but still erode margins, hurt customer experience, and damage brand trust. IPQS VP of Fraud Strategy Alexander Hall argues that focusing solely on chargeback rate can hide bigger issues affecting long-term growth." }, { "q": "Which industries are seeing the biggest rise in account takeovers?", "a": "Ecommerce and airlines are experiencing a troubling rise in account takeovers (ATOs), according to Hall. The pattern extends across other sectors as well: iGaming platforms are seeing fraudulent withdrawals after account changes, banking is facing a surge in synthetic identity fraud, and money movement platforms are dealing with identity theft used to create and operate fraudulent businesses." }, { "q": "What metrics does IPQS recommend tracking alongside chargebacks?", "a": "IPQS recommends tracking approval rate for good customers, false positive rate or 'good customer decline' rate, manual review rate and average decision time, volume and value of fraud-related refunds or credits, abuse rates for promotions, referrals, and loyalty programs, and account takeover incidents and new account abuse volume. These metrics provide a fuller picture of fraud impact on revenue, costs, and growth." } ]