Stop ecommerce fraud
before it drains your revenue

Ecommerce fraud is any deceptive activity targeting online stores or their shoppers, and it splits into two layers that need different tools. Transaction layer: fraudulent payments and orders: chargeback fraud, friendly fraud, card-not-present fraud, card testing, and return or refund fraud. Covered by a chargeback-prevention or payment-fraud platform; Account layer: one person operating many accounts to claim discounts, coupons, welcome offers, referral credits, and loyalty rewards more than once (multi-accounting, account farms), plus account takeover of real customers' logins. Covered by an account-layer identification tool. ShieldLabs covers the account layer. It detects High-Risk Events such as Multi-accounting (one person behind many accounts) and Account takeover (logins from unrecognized devices), using persistent visitor and user identification that holds across sessions regardless of email, IP, or cleared cookies.

You prevent ecommerce fraud by stacking a few layers, because no single tool covers all of it. Most stores run two or three of these together: Payment layer: a chargeback-prevention or payment-fraud platform screens transactions, cards, and card-not-present risk; Authentication layer: multi-factor authentication, strong password rules, and step-up checks on high-risk logins cut down account takeover; Policy layer: your store's own promo rules: limits per customer, device, payment card, or shipping address; rate-limits on coupon redemption; delayed reward payouts; Account layer: an identification tool detects one person operating many accounts and logins from unrecognized devices, so you can hold or step up before a discount is issued. ShieldLabs is the account layer. It returns a risk score, a signal breakdown, and High-Risk Events on the first visit, so you can act before a discount is claimed or a reward is paid.

ShieldLabs runs through a single JavaScript snippet on your signup, login, or account page and returns what you need to act on a high-risk account before a discount is issued. On every visit it returns: A 0-100 risk score with a per-signal breakdown; Persistent visitor and user identification that holds across cleared cookies, incognito mode, and rotated IP; Risk signals: VPN, proxy, Tor, anti-detect browser, and IP reputation; High-Risk Events with Medium or High confidence, including Multi-accounting and Account takeover; when many signups trace back to one device, browser, or identity, ShieldLabs detects Multi-accounting directly. ShieldLabs delivers the risk score, signals, and events in the analytics dashboard and via API and Webhooks, so you can flag, hold, or step up an account before a reward is paid.

Yes. ShieldLabs stops promo and coupon abuse by detecting the multi-accounting behind it, so you can hold or limit a discount before it is issued. Promo and coupon abuse is mostly one person creating many accounts to claim a first-order discount, a welcome offer, or a referral credit more than once. It links those accounts through accurate identification, even across cleared cookies and rotated IP; It detects Multi-accounting when many signups trace back to one device or identity, so you see the abuse in the analytics dashboard; It returns the score, the signal breakdown, and the High-Risk Event with Medium or High confidence via API and Webhooks. ShieldLabs helps block the abusive account before a discount is issued.

Yes. The mechanism is the same wherever one person can profit by opening many accounts or by getting into an account that is not theirs, so the same signals apply across store types. ShieldLabs detects Multi-accounting and Account takeover at signup and login, and you act on the downstream abuse each store cares about: DTC brands and online retail: first-order-discount farming and coupon stacking; Subscription commerce: free-trial cycling and welcome-offer abuse; Loyalty and rewards programs: points inflation and referral-credit fraud; Any store with a login: account hijacking and the support cost of recovering compromised accounts. ShieldLabs identifies the visitor and user behind each account at the signup and login layer, so you can choose to allow, hold, or step up each account.

Yes. ShieldLabs gives stores of any size enterprise-level functionality without enterprise pricing, and it turns on self-serve without a sales call, so your team can act on a risk score instead of reviewing accounts by hand. A small or mid-sized store loses real money to the same account abuse a large one does, one person farming first-order discounts, stacking coupons, or cycling welcome offers under fresh accounts. Sign up, add one JavaScript snippet to your signup and login pages, and you are running in about 5 minutes; The free tier includes 5,000 one-time identifications, no credit card required; Pick a plan by your traffic, so it fits a single store today and grows with a high-volume one. ShieldLabs detects High-Risk Events at signup and login, giving your team the detection depth big platforms build in-house, at transparent pricing.

Yes. ShieldLabs is ecommerce fraud prevention software for the account layer, a tool you integrate to surface fraud and abuse automatically rather than reviewing accounts by hand. It is software you integrate and run yourself, with detection ready out of the box. Installs as one JavaScript snippet on your signup, login, and account pages; Returns a risk score and risk signals through the API and Webhooks, with High-Risk Events visible in the analytics dashboard; Identifies the visitor and user, then detects Multi-accounting and Account takeover, so you can choose to allow, hold, or step up each account; Pairs with a dedicated payment-fraud platform for the payment and chargeback side, which it does not cover. ShieldLabs is the software that covers the fake-account, promo-abuse, multi-accounting, and account-takeover layer.

You integrate ShieldLabs by adding one JavaScript snippet to your signup, login, or account page; integration takes about 5 minutes. The steps: Install the snippet on your signup, login, or account page; Pass an optional UserHID (a hashed account or user identifier from your own system) once a shopper signs up or logs in; Read the risk score and risk signals via API and Webhooks for server-side flows; High-Risk Events are visible in the analytics dashboard. ShieldLabs returns the risk score and signals on the first visit, and the free tier includes 5,000 one-time identifications with no credit card, so you can test on real traffic before rolling out to production.

ShieldLabs detects risky accounts out of the box and helps block fraudulent and abusive traffic, while legitimate shoppers pass through. Every signup and login gets a 0-100 risk score in one of three bands, plus any High-Risk Events, and you choose the action for each case: Dangerous (60-100): hold a signup or a login for manual review; Suspicious (30-59): flag an account for review or a reduced discount; Trusted (0-29): let a legitimate shopper through with no extra steps. The free tier includes 5,000 identifications, so you can see results on real traffic before rolling out to production.