Digital platforms and e-commerce sites have increased the risk of fraud manifold. While stringent security measures minimise instances of fraud, they can inadvertently block many transactions that are legitimate. Interestingly, these ‘false positives’ can cost businesses 75 times more than the cost of fraud in the value of cancelled transactions and lost opportunities for further business.
Your fraud management system, therefore, has a threefold responsibility –
- To detect and prevent fraudulent activity
- To ensure that you do not block legitimate transactions in the process of minimizing your fraud rate.
- To enhance security without compromising customer satisfaction
It is worthwhile tracking a few KPIs to know if your current fraud management system can fetch the desired business outcomes. A fraud KPI, or fraud key performance indicator, is a measurable metric that shows how well your fraud management system is detecting and preventing fraud without blocking legitimate customers. Tracking the right fraud KPIs and metrics together, rather than any single number in isolation, is what gives you the fuller picture below.
Effective KPIs for fraud management
Most fraud prevention tools allow you to track useful metrics such as the percentages of approved transactions, declined transactions, and false positives. However, these values, taken in isolation, cannot give you a comprehensive picture of the overall performance of your fraud prevention software and strategies.
Here are seven effective KPIs for fraud management that will help your organisation balance security with customer satisfaction:
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Approval versus denial rate
Approval refers to the volume of transactions that receive the ‘approved’ status after the screening , a critical factor in evaluating your risk management strategy. This includes transactions approved by your fraud detection system and human teams. Your approval rates should be close to 80% unless you are in a high-risk business.
Denial rate refers to the number of transactions declined from the total transaction volume, a key performance indicator for assessing fraud management effectiveness. Denials can come from your fraud management system or analysts, card issuers, payment gateways, or chargebacks, impacting your overall fraud prevention efforts.
A high approval-to-denial ratio is among the best KPIs of fraud management. However, it is crucial to factor in the source of denials to enhance your risk management approach. For instance, if your denials stem mainly from chargebacks or if your chargeback rate exceeds 1%, it is time to tweak your fraud management system despite a high approval rate. Because most denials in a fraud management program trace back to payment sources like card issuers, gateways, and chargebacks, approval and denial rates also double as core payment fraud metrics worth watching on their own.
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Chargeback rate
Chargeback rate is the share of your approved transactions that customers or card issuers later dispute and reverse, usually reported as a percentage of total transaction volume or count over a given period. Unlike a denial, which stops a transaction before it settles, a chargeback happens after the fact, once money has already changed hands, which makes it a more expensive and more visible signal of missed fraud.
Most payment networks treat a chargeback rate above roughly 1% as high-risk, and sustained high rates can bring scheme fines or restrictions on your ability to process card payments at all, independent of any fraud losses themselves. Because a rising chargeback rate can point to a fraud management system that is approving transactions it should be catching, it is worth tracking as its own KPI rather than folding it into approval or denial rate alone, and worth reviewing alongside recall and precision to see whether the gap is a detection problem or a dispute-handling problem.
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Incoming pressure
Incoming pressure is the total volume of transactions identified as fraudulent, regardless of whether those transactions were approved or declined. In other words, incoming pressure measures how much fraudulent traffic your organisation faces in a specific period.
Tracking this fraud management KPI can tell you whether your approval and denial rates align with your industry standards and help you reduce fraud effectively.
For instance, an 80% approval rate is reasonable if your incoming pressure is high but suboptimal if the incoming pressure is low. Similarly, if your incoming pressure and denial rates are inversely proportional, you should reassess your fraud management system strategies to ensure optimal performance and fraud prevention success.
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Precision versus false positives
This is a crucial fraud management KPI to balance security with customer satisfaction. Of the total volume of declined transactions, precision is the percentage of fraudulent transactions, while false positives are legitimate transactions misidentified as fraud which can affect your fraud KPI. In other words, precision is your ‘hit rate’ and false positives are your ‘miss rate’ in the context of payment fraud.
False positives indicate a subpar customer experience, costing you sales, business opportunities, and customers. Keeping your precision percentage high and your false positives minimal is vital. Precision and false-positive rates are two of the most closely watched fraud detection metrics, since they measure directly how accurately your system tells real fraud apart from legitimate activity.
But it is also important to remember that the precision metric only refers to declined transactions correctly identified as fraud, which is crucial for accurate fraud KPI assessment. It does not apply to fraudulent transactions that get processed and approved. A high precision percentage, therefore, may not indicate optimal performance.
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Recall
Out of the total number of approved and denied transactions your organisation eventually tags as fraud, recall, or ‘catch-rate’ is the number of cases your fraud management system has declined before processing.
A high recall is the gold standard of an optimally functioning fraud management system. Your precision metric has little value if your recall rate is low, especially in the face of rising fraud cases. You can maximise recall by investing in an AI-driven fraud management system that accurately scores the risk level in every transaction.
Your recall and precision metrics, taken in combination, should justify your decline rate and reflect the effectiveness of your fraud prevention efforts. If your decline rate is substantially higher than your recall and precision, it means your fraud management system is blocking too many legitimate transactions, contributing to a higher fraud rate.
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Fraud-to-sales (F2S) ratio
The F2S ratio is the volume of fraudulent transactions divided by the total transaction volume in your organisation, serving as a key performance indicator for fraud management. Ideally, your F2S ratio should not exceed 1%, but this percentage is industry-specific and reflects current fraud trends. This is a useful fraud management KPI to ensure that your organisation’s security levels meet industry standards.
A sharp rise in your F2S ratio calls for reassessing your security systems or fraud prevention strategies to effectively mitigate payment fraud.
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Good user approval rate
A good user approval rate is the percentage of ‘good users’ or legitimate transactions from the total volume of approved transactions, essential for maintaining a healthy checkout process. This is perhaps the most important KPI of fraud management, as the prime objective of a fraud prevention system is to maximise legitimate transactions and minimise false positives while effectively managing fraud cases.
Comparing the relative values of your good user approval rate, overall approvals, and incoming pressure can give you a good idea of the efficiency of your fraud tool.
How can Infosys BPM help with Fraud Management KPIs?
Balancing fraud management with customer satisfaction is challenging for most organisations. With our comprehensive set of fraud detection and prevention analytics tools, we help organisations analyse massive and complicated data sets to detect irregularities, eliminate false positives, and deliver comprehensive, advanced fraud control solutions.
Know more about Infosys BPM’s fraud management solutions.
Frequently asked questions
Individual fraud KPIs mean little to a CFO on their own. What lands is showing the trade-off together: your approval rate and good user approval rate against the cost of false positives, set beside your F2S ratio and incoming pressure. That combination turns fraud KPIs into a business case, showing leadership what fraud prevention is protecting and what over-blocking is costing in lost legitimate sales.
Recall and precision carry the most weight for real-time fintech fraud detection, since decisions have to happen in milliseconds with no time for manual review. Incoming pressure also matters more here than in slower-moving industries, because fintech fraud volumes can spike quickly and a fraud management system needs to be judged against that changing baseline, not a fixed target.
In practice they overlap, but a fraud metric is any raw number you can measure (declined transactions, chargeback count), while a fraud KPI is a metric your organisation has chosen to track deliberately because it indicates performance against a goal, like keeping approval rates near 80% or F2S under 1%. Every fraud KPI is built from one or more underlying fraud metrics.
Yes. Common benchmarks, like an 80% approval rate or a sub-1% fraud-to-sales ratio, are general starting points, not fixed rules. Regulated industries and high-risk categories typically run stricter denial thresholds and closer scrutiny of approval sources, which is why the 80% approval guideline only holds outside high-risk businesses.
Operational teams typically watch approval, denial, and false-positive rates on a daily or weekly dashboard, while trend KPIs such as F2S ratio, chargeback rate, and incoming pressure are reviewed monthly or quarterly. Two events should always trigger an out-of-cycle review: any change to your fraud rules or scoring model, and a sudden spike in incoming pressure, since yesterday's thresholds may no longer fit today's attack pattern.
