> For the complete documentation index, see [llms.txt](https://docs.bloop.plus/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.bloop.plus/best-practices/preventing-fraud.md). # Preventing Fraud Every reward you pay is only worth it if a real new customer is on the other end. The short answer: leave Bloop's automatic fraud signals on so abuse is caught before a reward leaves your account, but review each held case on its evidence rather than rejecting on sight — and use your offer settings to remove the incentive to cheat in the first place. This article explains how to treat fraud control as a budget control, then links the Bloop settings involved. The most common abuse is self-referral: one person posing as both referrer and referee to claim both sides of the deal. Heavy-handed blocking stops that but also frustrates genuine power users; the goal is to catch the few abusers without taxing the many honest customers. ### Let detection do the watching Instead of auditing every referred order, let Bloop watch for the patterns abuse leaves behind and surface only the orders that deserve a second look. When a referred purchase trips a signal, Bloop flags it, holds the reward, and opens a case for your decision. Genuine referrals flow through untouched. | Signal | What it catches | | --------------------- | ------------------------------------------------------------------------------------- | | Self-referral email | Referrer and referee emails that look like the same person after normalizing aliases | | Repeated same IP | Several referred purchases for one referrer from the same IP in a recent window | | High volume in a week | One referrer driving an unusually high number of referred purchases in a short window | Keep these on. They are your first and cheapest line of defence. ### Review held cases on evidence, not suspicion A flag is a prompt to look, not a verdict. A power user on a shared office or household network can look a lot like collusion. When reviewing the [Fraud center](/referral-program/management/fraud-center.md) queue: * **Trust** genuine referrers who keep tripping a signal for innocent reasons, so future orders from them flow through. * **Ban** only clear abusers. * Judge the held order on its own evidence rather than rejecting any flagged order automatically. ### Remove the incentive to cheat at the source The cheapest fraud to prevent is the kind your offer never invited. Several offer-level choices quietly reduce abuse: * **A minimum purchase requirement** makes self-referral unprofitable, because the abuser has to spend real money to claim a reward worth less. * **A reward review period** adds a short delay before approval, giving signals time to surface before money moves. Suspicious orders are held separately regardless. * **A tighter audience** — for example restricting referring to prior buyers or a customer tag — narrows the pool of people who can game the program. Open wide at launch to gather data, then tighten only if abuse appears. ### Match scrutiny to risk Not every program needs the same vigilance. A high-value cash reward on a wide-open audience deserves close review; a modest store-credit reward gated to past customers carries far less risk and rarely needs hands-on attention. Calibrate your review effort to what a successful abuse would actually cost you. ### Set it up in Bloop * Review and resolve flagged orders in the [Fraud center](/referral-program/management/fraud-center.md). * Add minimums and a review period in [Set up referrer and referee rewards](/referral-program/rewards.md). * Tighten who can refer in [Target audience](/referral-program/target-audience.md). * To understand the patterns behind the flags, read [how to prevent referral fraud](https://bloop.plus/blog/referral-fraud/) and [what self-referral is](https://bloop.plus/blog/self-referral/). ### Related * [Best practices: designing your referral offer](/best-practices/designing-your-offer.md) * [Fraud center](/referral-program/management/fraud-center.md) * [How to prevent referral fraud](https://bloop.plus/blog/referral-fraud/) --- # Agent Instructions This documentation is published with GitBook. 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