Build a Custom Fraud Dashboard Using AI in Minutes
Describe your Fraud Dashboard in plain English and create a production-ready build, from design and development to deployment, in minutes. No code needed.
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Emergent Key Features for Building a Fraud Dashboard
Rule performance measured against confirmed outcomes, with the cost of friction shown alongside losses prevented.
Rules Judged on Outcomes
Each rule is measured against confirmed fraud rather than alerts raised, which identifies the rules generating work without protecting value.
False Positive Cost in Currency
Legitimate transactions blocked are valued, so tightening a rule is assessed against the revenue it would cost.
Missed Fraud Analysed
Losses that passed every active rule are examined, showing where the rule set has a genuine gap rather than needing more sensitivity.
Review Capacity against Queue
Alert volume is compared with analyst capacity, so a rule change that would swamp the team is identified before it is deployed.
Rule Overlap Identified
Cases caught by several rules at once are surfaced, which is how a rule set gets simplified rather than continually extended.
Repeat Good Customers Flagged
Legitimate customers challenged repeatedly are identified, because that is where fraud prevention quietly damages retention.
Fraud Dashboard Use Cases You Can Build in Minutes
Remove the Rules That Only Create Work
Each active rule with alerts triggered, confirmed fraud caught, false positive rate and the legitimate value blocked, rules firing frequently with almost no confirmed fraud, rules not fired in ninety days, overlapping rules and the net value each protects.
window.awbMockup = { rulePerformance: "Build a fraud rule dashboard showing each active rule with alerts triggered, confirmed fraud caught, false positive rate and the legitimate value blocked, rules firing frequently with almost no confirmed fraud, rules that have not fired in 90 days, overlap where several rules catch the same cases, and the net value each rule protects.", reviewQueue: "Build a fraud operations dashboard showing cases awaiting review by risk score and age, cases breaching your review time target, analyst decisions per hour and approval rate by analyst, cases auto approved and auto declined against those reviewed, queue volume against available review capacity, and cases escalated for investigation.", fraudLoss: "Build a fraud loss dashboard showing confirmed fraud value by type, channel and payment method, loss as a share of transaction volume against target, chargebacks by reason with recovery outcomes, loss by customer tenure and geography, first party against third party fraud, and losses that passed every active rule.", falsePositives: "Build a fraud friction dashboard showing legitimate transactions declined or challenged, the revenue value of those declines, customers who abandoned after a challenge, false positive rate by segment and payment method, good customers repeatedly flagged, and the revenue recovered by relaxing a specific rule."};
Match the Queue to Your Review Capacity
Cases awaiting review by risk score and age, cases breaching your review time target, analyst decisions per hour and approval rate by analyst, cases auto approved and auto declined against reviewed, queue volume against capacity and escalations.
window.awbMockup = { rulePerformance: "Build a fraud rule dashboard showing each active rule with alerts triggered, confirmed fraud caught, false positive rate and the legitimate value blocked, rules firing frequently with almost no confirmed fraud, rules that have not fired in 90 days, overlap where several rules catch the same cases, and the net value each rule protects.", reviewQueue: "Build a fraud operations dashboard showing cases awaiting review by risk score and age, cases breaching your review time target, analyst decisions per hour and approval rate by analyst, cases auto approved and auto declined against those reviewed, queue volume against available review capacity, and cases escalated for investigation.", fraudLoss: "Build a fraud loss dashboard showing confirmed fraud value by type, channel and payment method, loss as a share of transaction volume against target, chargebacks by reason with recovery outcomes, loss by customer tenure and geography, first party against third party fraud, and losses that passed every active rule.", falsePositives: "Build a fraud friction dashboard showing legitimate transactions declined or challenged, the revenue value of those declines, customers who abandoned after a challenge, false positive rate by segment and payment method, good customers repeatedly flagged, and the revenue recovered by relaxing a specific rule."};
Find Where the Losses Got Through
Confirmed fraud value by type, channel and payment method, loss as a share of transaction volume against target, chargebacks by reason with recovery outcomes, loss by customer tenure and geography and the losses that passed every active rule.
window.awbMockup = { rulePerformance: "Build a fraud rule dashboard showing each active rule with alerts triggered, confirmed fraud caught, false positive rate and the legitimate value blocked, rules firing frequently with almost no confirmed fraud, rules that have not fired in 90 days, overlap where several rules catch the same cases, and the net value each rule protects.", reviewQueue: "Build a fraud operations dashboard showing cases awaiting review by risk score and age, cases breaching your review time target, analyst decisions per hour and approval rate by analyst, cases auto approved and auto declined against those reviewed, queue volume against available review capacity, and cases escalated for investigation.", fraudLoss: "Build a fraud loss dashboard showing confirmed fraud value by type, channel and payment method, loss as a share of transaction volume against target, chargebacks by reason with recovery outcomes, loss by customer tenure and geography, first party against third party fraud, and losses that passed every active rule.", falsePositives: "Build a fraud friction dashboard showing legitimate transactions declined or challenged, the revenue value of those declines, customers who abandoned after a challenge, false positive rate by segment and payment method, good customers repeatedly flagged, and the revenue recovered by relaxing a specific rule."};
Count the Revenue Caution Costs You
Legitimate transactions declined or challenged, the revenue value of those declines, customers who abandoned after a challenge, false positive rate by segment and method, good customers repeatedly flagged and the revenue recovered by relaxing a rule.
Count the Revenue Caution Costs You
Legitimate transactions declined or challenged, the revenue value of those declines, customers who abandoned after a challenge, false positive rate by segment and method, good customers repeatedly flagged and the revenue recovered by relaxing a rule.
Build a custom fraud dashboard in 4 simple steps
Track alerts, rule performance and losses against the friction you create, so fraud prevention is tuned rather than tightened until customers complain.
Start with fraud loss and recovery, alert volume and review capacity, false positive rate, transactions declined that were legitimate, and the customer segments most affected. Emergent builds around your rules and risk appetite rather than a generic alert log.
Link transaction data, your rule or model decisions, manual review outcomes and confirmed fraud and chargeback records. Emergent measures each rule against what actually turned out to be fraudulent, which is how a rule set gets tuned instead of accumulating.
Ask to relax a rule, add a new one, change a review threshold or alter how false positives are valued, and the effect on both losses and friction is recalculated.
Deploy one build where analysts work the review queue with context attached and leadership sees loss, friction and capacity together. A rule change is assessed on both sides rather than only on fraud caught.
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Why choose Emergent?
Most tools give you a demo you have to rebuild. Emergent gives you a product that is ready to run.
| Comparison | Other Tools |  |
|---|---|---|
| Built for | Demos and MVPs | Products you keep growing |
| What you get | Front end shell only | Full stack, wired end to end |
| Backend and database | Set it up yourself | Built and connected for you |
| Customization | Surface level styling | Deep workflow control |
| Integrations and APIs | Manual glue work | Connected from a prompt |
| Code ownership | Locked to the platform | Clean code you can export |
| Time to launch | Weeks of patching and setup | Live the same day |
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