Fraud & Transaction Risk Monitor · Banking & Compliance
Put risky transactions in front of an analyst within minutes
Scores each transaction 0–100 against the fraud rules you write, explains why, and holds high-risk cases in Reviews. Your analysts make every call.
Free account to start. Buying and running live need a paid plan.
- Starts when your form or app sends it something
- 1 AI step
- A person approves before it acts
- About 25 min to set up
Sound familiar?
The job, before and after this agent.
What it feels like today
- “By the time we spot a suspicious order, the goods have shipped.”
- “Our fraud rules live in someone's head and get applied unevenly.”
- “Analysts waste time on low-risk alerts while real cases wait.”
What you get with the agent
- A 0–100 risk score from your written rules plus AI judgement over the history you send
- The rules that fired and the anomalies, with evidence from the transaction
- A case summary and a neutral verification message draft for the analyst
- High-risk transactions posted to your fraud channel and held in Reviews; confirmed cases logged in Google Sheets
- Medium-risk ones added to a review queue sheet; low-risk ones kept in run history
Before
Analysts scan processor dashboards, apply rules from memory and note cases in a spreadsheet when they remember.
After
High-risk transactions arrive in Slack with a score, the rules that fired and a draft verification message. The analyst decides and acts in your own systems.
How it works
The whole workflow, step by step.
Receives each transaction, with any customer history you have, from your processor, core system or store through a webhook. AI scores it 0–100 against the fraud rules you write and the history sent, lists the rules that fired and anomalies with evidence, and writes a case summary and a neutral verification message draft. High-risk transactions are posted to your fraud channel in Slack and held in Reviews for an analyst; confirmed cases are logged in a Google Sheet. Medium-risk ones go to a review queue sheet. It never blocks, refunds or contacts anyone: your analysts act in your own systems.
- TriggerNew transaction
- AI stepScore the transaction
- LogicHigh, medium or low risk?
- High:Alert the fraud team in Slack
- High:Analyst decides
- Medium:Add to the review queue sheet
- Low:Keep low-risk in history
- App callAlert the fraud team in Slack
- OutputFraud team alerted
- Human approvalAnalyst decides
- Confirmed:Log the confirmed case
- App callLog the confirmed case
- App callAdd to the review queue sheet
- OutputKeep low-risk in history
This is the workflow that opens in your workspace when you set the agent up. Every step can be edited.
- Step 1New transactionYour payment processor, core system or store posts each transaction (with any customer history you have) to the webhook URL.
- Step 2Score the transactionAI checks the transaction against your fraud rules and the customer history you send, scores the risk 0–100, lists the rules hit and writes a case summary.
- Step 3High, medium or low risk?Scores of 70 or more go to an analyst now; 40–69 go to the review queue sheet; the rest are kept in the run history. Change the numbers on the router to tune it.
- Step 4Alert the fraud team in SlackPosts the transaction, score, rules hit and case summary to your fraud channel so an analyst looks now.
- Step 5Fraud team alertedThe run history keeps the alert that was posted.
- Step 6Analyst decidesA fraud analyst reviews the case in Reviews and takes any action (hold, refund, block, contact the customer) in your own systems; approving logs the case as confirmed for follow-up.
- Step 7Log the confirmed caseAppends the case to your fraud case log sheet for follow-up and reporting.
- Step 8Add to the review queue sheetMedium-risk transactions are appended to your review queue sheet for an analyst to check in their next pass.
- Step 9Keep low-risk in historyLow-risk transactions are kept in the run history with their score; nothing is flagged.
Example run
What goes in, and what comes out.
Example with fictional data
Comes in
A fictional $2,480 card-not-present electronics order from a 6-day-old account, IP country different from billing, new shipping address, 3 failed attempts in 24 hours.
The agent produces
Score 88, high risk. Rules fired: new account, country mismatch, failed attempts, amount far above the customer's average. Posted to #fraud with a case summary and a neutral verification email draft, held for an analyst.
What you need
Everything it takes to run it.
About 25 minutes from purchase to live. A checklist above the canvas takes you through each step.
Plan
Included in Enterprise; on other paid plans it's $199 once. Agents run live on paid plans, from Basic ($39/mo).
Your AI key
Connect any of 14 AI providers on your own key. Your provider bills usage directly, at cost; we add no markup.
Apps
- SlackLive
- Google SheetsLive
Checklist
- A paid plan (agents run live on paid plans).
- An AI provider key (Settings → AI Providers).
- Slack and Google Sheets, connected in Settings → Integrations.
- A processor, core system or store that can send each transaction (ideally with customer history fields) to a webhook URL.
Setup, about 25 minutes
- Connect your AI provider. The AI steps run on your own key (OpenAI, Anthropic, Google and more). Add one in Settings → AI Providers.
- Connect Slack. Connect the Slack workspace your fraud team uses (Settings → Integrations → Slack).
- Connect Google Sheets. Connect the Google account that can edit your fraud case log (Settings → Integrations → Google Sheets).
- Write your fraud rules. Open “Score the transaction” and replace the placeholder with your rules. The score is only as good as these rules and the history you send.
- Pick the Slack account and fraud channel. Open “Alert the fraud team in Slack” and pick your account and channel. Invite the app to private channels first (/invite @Fluxo Flow).
- Pick your case log and review queue. Open “Log the confirmed case” and “Add to the review queue sheet” and pick your account, spreadsheet and tab in each. Header row: Time, Transaction, Customer, Amount, Currency, Channel, Score, Level, Rules hit, Summary, Status.
- Test it with Dry Run. Press Dry Run: the agent runs on sample data with no messages sent and nothing written to your apps.
- Switch the trigger on. Open the trigger, switch the webhook on and have your processor, core system or store send each transaction to its URL.
Is it a fit?
Who it's for, and what it won't do.
Built for
- E-commerce merchants selling high-value goods
- Fintechs and payment companies with a small risk team
- Fraud and risk analysts at credit unions
What it doesn't do
- It never blocks, holds, refunds or cancels a payment, or contacts a customer: “hold” means it waits in Reviews, and your analysts act in your own systems.
- It isn't a trained fraud model and doesn't replace your processor's fraud tools; it applies your written rules plus AI judgement to the data sent.
- It doesn't fetch history from Stripe, Square or Shopify itself; send the context with each transaction.
- It never uses protected characteristics or names as risk signals.
We list the limits up front so you can decide before you buy.
Price
$199 one-time
Per workspace. It never renews.
- Included at no extra cost on Enterprise.
- Buying and running it live need a paid plan, from Basic ($39/mo).
- Dry Run costs nothing: simulated AI and app calls, nothing sent.
- AI usage is billed by your own provider, at cost. No AI credits to buy from us.
One-time agent purchases aren't covered by the 30-day money-back guarantee. Refund policy
FAQ
Questions about Fraud & Transaction Risk Monitor.
Will it block payments or contact customers?
No. “Hold” means the case waits in Reviews. Any block, refund or customer contact is done by your team in your own systems.
Is it a trained fraud model?
No. It applies your written rules plus AI judgement to the data you send, and it doesn't replace your processor's fraud tools. It never uses protected characteristics or names as risk signals.
How does it get transaction data?
Your processor, core system or store sends each transaction, ideally with history fields, to its webhook. It doesn't fetch history itself. Setup takes about 25 minutes.
Is it worth the price?
It's a one-time purchase that never renews, and it applies your rules to every transaction, not just the ones someone happens to look at. Live runs need a paid plan and your own AI key; Dry Run is free.
Can it listen to Stripe, Square or Shopify directly?
Send their events to the webhook from your own system, or switch the trigger to the Stripe, Square or Shopify app trigger in its settings once that app is connected (those apps are still waiting for vendor approval).
Does it block or refund payments?
No. “Hold” means the case waits in Reviews for an analyst. Any hold, refund or block is done by your team in your processor.
Does it learn each customer's behaviour?
It compares the transaction with the history fields you send (average amount, usual country, recent count…). It doesn't build or store its own model.
Is this a subscription?
No. Fraud & Transaction Risk Monitor is a one-time purchase of $199 per workspace and never renews. The Enterprise plan includes it at no extra cost. Running it live needs a paid plan (from Basic ($39/mo)), and your AI provider bills you directly for usage.
Can I test it before it touches real data?
Yes. Once it's set up in your workspace, Dry Run plays every step on sample data with simulated AI and app calls: nothing is sent and nothing in your apps changes. Switch the trigger on only when you're happy.
Put Fraud & Transaction Risk Monitor to work.
Free account, no credit card. Your Agents page opens with Fraud & Transaction Risk Monitor ready to buy and set up, then Dry Run it before it goes live.