Duplicate and synthetic applicants
One operator opens many accounts to collect sign-up credit or to pass early checks. One device behind several new accounts is visible once the visitor ID is stored with each.
Onboard quickly. Without onboarding fraud.
Fintech fraud prevention starts with knowing the device behind every application, login and transfer. Fingerly gives each one a visitor ID, the signals around it and a suspect score, so your team steps up verification only where the evidence asks for it.
- A visitor IDFor every application and login.
- Takeover signalsNew device, Tor, automation.
- Banking appsRooted, jailbroken and hooked devices.
- Your policyWeights and a threshold you set.
[ 01 / 06 ]Abuse patterns
How abuse reaches fintech.
The same few patterns recur wherever money moves. Each one leaves a trace on the device or the network that an email address and an IP address alone do not show.
Account takeover
Stolen credentials are tried at login and password reset. An unfamiliar device on an automated or anonymised network is the pattern to separate from the customer.
Credential stuffing
Scripts replay leaked passwords against your login at speed. Driven browsers, virtual machines and unusually busy devices are reported without a captcha.
Payee and card changes
Adding a payee, a card or a payout destination right after a login from a new device is a common step in a takeover, and a good moment for a second check.
Referral and bonus farming
Refer-a-friend and welcome bonuses attract farms of near-identical devices. Device farm and emulator signals make the cluster visible before the payout.
Compromised mobile devices
Banking apps run on devices that are rooted, jailbroken or instrumented. The native SDKs report those states so a sensitive action can be treated with care.
[ 02 / 06 ]Pattern to decision
From pattern to decision.
Each pattern maps to what Fingerly reports on the request and to the first decision teams usually make. The decision is always yours.
01
Duplicate applicants
Link the fifth application to the first four.
Store the visitor ID with each application and count accounts per device. Device farm, emulator and anti-detect browser signals make a cluster more telling. The usual first decision is to hold promotional credit and send the cluster to review.
- Check at
- ApplicationAccount opening
- Reads
- Visitor IDNew or returningDevice farm
02
Takeover at login
A known password from an unfamiliar device.
Recognise the devices an account normally signs in from. A new device is not suspicious alone; a new device that is also automated or on a Tor exit node is. The usual first decision is a second factor for that login only.
- Check at
- LoginPassword reset
- Reads
- Visitor IDTor exit nodeAutomation
03
Changes to money movement
The riskiest minute of a session.
Identify before a payee, a phone number or an email address is changed, and again at a large transfer. Read the suspect score and the tampering signals together, and confirm with the customer above the threshold you choose.
- Check at
- Adding a payeeChanging contact detailsLarge transfers
- Reads
- Suspect scoreTamperingVisitor ID
04
Compromised app environments
What the phone says about itself.
In iOS and Android apps, instrumentation, traffic interception, rooted and jailbroken devices and cloned apps are reported as signals with weights you control. In an app the device is recognised by a random install ID the SDK keeps for the app, never by its hardware.
- Check at
- App loginTransfersChanging payees
- Reads
- InstrumentationInterceptionRooted deviceJailbroken device
[ 03 / 06 ]Integration
Integrate at the right moments.
Four habits keep a policy for fintech effective without turning it against genuine customers. A production identification is billed per request, from $0.0025, so it is worth placing where it earns its cost.
- 01 Identify at the moment
Call identify when someone applies, signs in, resets a password or adds a payee, not on every screen. Pass your own reference as the tag so each result comes back with the account it belongs to.
await fingerly.identify({ tag: "login" }) - 02 Verify on your server
Send only the request ID from the browser or app to your backend, read the stored result there with a secret key, and check that its tag matches the action. Never act on what the client reports about itself.
- 03 Observe before you enforce
Run in monitoring mode first. Record what each rule would have done, measure how many genuine customers it would have affected, and only then turn it on.
- 04 Act in proportion
Allow familiar devices, add a second factor for new ones that carry other signals, and send clusters to review. Keep a recovery path for the customer who is caught by mistake.
[ 04 / 06 ]Moments
Where to check, what to do.
A short map of where a fintech product usually places the check and what it reads there.
| Moment | Identify when | Read | Usual first decision |
|---|---|---|---|
| Account opening | The application is submitted | Visitor ID, new or returning, device farm | Hold promotional credit and review clusters |
| Login | Credentials are submitted | Visitor ID, automation, network signals | Allow familiar devices, step up for new ones with other signals |
| Password reset | Before the reset link is sent | Visitor ID, Tor exit node, high activity | Rate limit or step up |
| Adding a payee | Before it is saved | Visitor ID, tampering | Ask for a second factor |
| Large transfer | At confirmation | Suspect score, instrumentation, interception | Confirm with the customer above your threshold |
Every decision is yours. Fingerly returns the visitor ID, the signals and the suspect score, and never blocks a request by itself.
[ 05 / 06 ]Questions
Questions about fintech.
What device fingerprinting does for a financial product, and what it deliberately leaves to your other systems.
Talk to the teamHow does Fingerly help fintech companies prevent fraud?
Fingerly gives a fintech product a visitor ID for the device behind each signup, login and money movement, plus signals for bots, VPNs, proxies, Tor, emulators and tampering, and a suspect score under weights you set. Your own systems read that on the server and decide whether to allow, challenge, review or refuse.
Does device fingerprinting replace KYC or transaction monitoring?
No. Fingerly is an additional input to those decisions, not a substitute. It does not verify identity documents, authorise payments or monitor transactions; it describes the device and network behind a request so your existing checks have more to go on.
Can Fingerly spot account takeover in a banking app?
Fingerly reports the signals that usually surround a takeover: a new device, automation, an anonymised network and, in iOS and Android apps, rooted or jailbroken devices, instrumentation and interception. In an app the device is a random install ID, so combine the result with the account history you already hold.
Will it slow down onboarding for real customers?
Not noticeably. Fingerly shows no captcha and no permission prompt, and the browser SDK answers after an initial collection budget of 300 milliseconds. Genuine customers on a familiar device go straight through, and friction is kept for the sessions that carry evidence.
Is a visitor ID the same on the web and in the app?
Do not assume so. A browser and a native app describe a device differently, so Fingerly treats them as separate visitors. Connect the two through your own account records, which is where a customer is already one person.
Less guessing. More knowing.
Make the next connection a trusted one.
Start with the signals, keep your own decisions, and pay as you go, only for what you identify. No credit card needed.