“For most teams, fraud performance is still summed up in a single metric: chargeback rate.” That narrow focus, industry practitioners warn, leaves large swaths of cost and risk invisible — costs that hit revenue, operations, and customer trust long before a dispute becomes a chargeback.
Chargeback rate as the program north star — and its blind spots
According to Alexander Hall, the new VP of Fraud Strategy at IPQS, fraud teams often treat chargeback rate as the single, dominant performance signal because it is visible, painful, and tied directly to card network thresholds. In a discussion with Jordan Harris of The Fraud Boxer, Hall argued that this emphasis makes sense tactically but distorts the strategic picture: chargebacks are only one outcome of many, and focusing on them alone can hide larger problems that erode growth and margins.
Opportunity cost: the good customers you never see
IPQS highlights a class of losses that rarely show up in dispute metrics: legitimate customers who are declined or routed into slow manual reviews. False positives — when an IP, device, or email “looks risky” and blocks a real buyer — cause abandoned purchases and permanently lost lifetime value. From IPQS’ view, accurate risk scoring and tuning matter “as much as catching fraud itself,” because approval rate for good customers and the false positive rate determine revenue that never materializes.
Operational drag: manual reviews, support tickets, and rework
Every suspicious order sent to manual review adds labor cost, slows fulfillment, and creates friction for customers. IPQS cites a broad set of operational burdens: fraud-related tickets for refund requests, account lockouts, and disputes over promotional abuse accumulate in support queues and increase headcount needs. For high-volume merchants and platforms, these ongoing costs can rival direct losses from fraud.
Account takeovers and cross-industry patterns
IPQS reports a rise in account takeovers (ATOs) in ecommerce and airlines. The firm notes that successful ATOs can reverse years of work to create seamless user experiences by driving customer churn, increasing acquisition costs through negative word of mouth, and enabling off-platform identity theft through stolen personally identifiable information. ATOs also create direct reimbursement liabilities, including for stolen stored value such as loyalty points.
Similar abuse patterns are appearing across other verticals: iGaming platforms see fraudulent withdrawals following account changes; banking faces a surge in synthetic identity fraud; and money-movement platforms confront identity theft used to create and operate fraudulent businesses. Those examples underscore IPQS’ point that fraud is not a single-mode problem but a set of related attack vectors with distinct operational and financial footprints.
IPQS scoring and the metrics that broaden visibility
IPQS positions its scoring approach as a visibility tool rather than a pure payments blocklist: it evaluates signals across IP reputation, device intelligence, email history, and past abuse patterns — not just payment details. The company recommends tracking chargebacks alongside a set of additional metrics that reveal broader impact:
- 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
When those signals align with outcomes data, IPQS argues, “your fraud metrics evolve from ‘chargebacks this month’ to ‘total impact on revenue, costs, and growth.’” The stated program goals are explicit: catch more fraud before it becomes a chargeback, reduce friction and false positives for legitimate customers, identify patterns of abuse in accounts and traffic sources, and feed more accurate data back into internal reporting and decisioning.
What this means for technologists, product leaders, and marketing
- Technologists and security teams: should prioritize richer signals — IP reputation, device intelligence, email history, past abuse — to detect patterns before they produce chargebacks and to reduce false positives that harm conversion.
- Product and operations leaders: need to measure manual review rate and average decision time, and to account for the operational drag that fraud creates in support queues and fulfillment pipelines.
- Marketing and growth teams: must track abuse rates for promotions, referrals, and loyalty programs and work with risk and finance to maintain a shared view of fraud impact so growth programs can scale safely.
If chargebacks are only one symptom, the remedy is a redesign of fraud programs around a wider set of outcomes: protecting customer experience, enabling safe marketing scale, and giving leaders confidence that controls support long-term growth rather than simply limiting transactions. IPQS offers its scoring and visibility tools to plug those gaps and invites teams to trial the approach; whether organizations will shift measurement and incentives away from a single metric remains the practical question.
