Fintech Fraud & Abuse Prevention
Fintech fraud prevention.
Protect customer access.
Bots, repeat accounts and account takeover create risk around financial web products. ShieldLabs provides ready-made detections and identification risk assessments to help protect signup and sensitive account access.
Start FreeWelcome back
Access your account.
Anti-Detect BrowserProxy
Protect onboarding capacity
Keep automated signups from overwhelming your product.
Expose repeat accounts
Detect multi-accounting across different registration emails.
Keep accounts secure
Protect customer access and sensitive web actions.
Welcome trusted customers
Use ready-made assessments to reduce unnecessary checks.
Web onboarding
Detect risky signups.
Protect genuine acquisition.
ShieldLabs detects bots, multi-accounting and disguised browsers around web registration. Help protect digital-wallet, online-lending and BNPL onboarding before account access and promotional benefits are granted.
Sensitive account access
Stop account takeovers.
Protect customer trust.
ShieldLabs detects account takeover and impossible travel around sign-in and sensitive web actions. Help protect established accounts before transfers, withdrawals and payment-detail changes.
Welcome familiar customers
Recognize returning visitors so existing sign-in flows can reserve extra checks for risky access.
Expose disguised access
Detect proxies, anti-detect browsers and location spoofing around sensitive account actions.
The ShieldLabs platform
More than one fraud check.
Protect your entire product.
Connect identification, device and network intelligence, bots, named risk signals and ready-made account abuse detections. Traffic quality analytics gives the sources behind risky activity.
Enterprise-level functionality. Without enterprise pricing.
Accurate identification
Recognize returning visitors even when they clear cookies, use incognito mode or change their IP address. Detect linked users with different email addresses.
Identification accuracy
High-Risk Event detection
Detect account abuse out of the box by automatically identifying linked users. No fraud model training is required.
Risk signals
Get ready-made detections of automation, masking and spoofing, with named risk signals behind each result.
Bot & AI traffic detection
Detect bot activity from browser automation signals. Recognize useful crawler and AI traffic alongside abuse detections.
Risk scoring
Score every visit from 0 to 100 and classify it as trusted, suspicious or dangerous. See the signals behind each score.
Device fingerprinting
Recognize devices by their fingerprints. Identify the browser, operating system and device type. Detect headless browsers and tampering.
IP & Network Intelligence
Reveal the real IP address and geolocation behind masking. Detect VPNs, proxies and private relays.
203.0.113.42198.51.100.23Traffic quality scoring and risk analytics
Get one score for all your traffic and ready-made quality results by source, channel, referrer and UTM campaign.
Analytics dashboard
Find risky accounts and visits.
See the sources behind them.
Explore visitors, users, devices and IPs with detected account abuse and identification risk assessments. See traffic quality by channel, referrer and campaign.
How it works
Start protecting your product.
Connect once and start receiving ready-made fraud and abuse detections.
- 01
Add the snippet or SDK
Connect your product and start identifying visitors and users.
- 02
Receive ready-made detections
Get detected fraud and account abuse in the dashboard or through API integrations.
- 03
Prevent fraud and abuse
Protect customer accounts, paid access and signup incentives in your product.
Developers
Integrate in
5 minutes.
A single API to identify, detect and score. Receive risk data through API responses and webhooks. Integrate selected data points into your business logic to prevent fraud and abuse.
Protect your users and product
Protect onboarding.
Secure customer access.
Start Free FAQ
Understand the evidence.
Put it to work.
What is account fraud in financial web products?
Account fraud includes fake or repeated registrations and unauthorized access to existing customer accounts, used to misuse a product or its services.
How does ShieldLabs help prevent fraud and abuse in Fintech?
ShieldLabs detects multi-accounting, bots and account takeover around web onboarding and sensitive account access. Ready-made risk assessments help protect access, incentives and legitimate customers.
Can ShieldLabs detect repeat onboarding with different emails?
Yes. Multi-accounting detection connects registered web accounts with different emails, while bot detection exposes automated registration attempts.
Does visitor recognition work after cookies are cleared?
Yes. ShieldLabs recognizes returning visitors across new sessions, cleared cookies, incognito browsing and IP changes. These are visitor-recognition capabilities.
How do I integrate ShieldLabs?
Add the browser snippet or client SDK to your web product. Receive identification results, risk signals and account abuse detections through the dashboard, API integrations and webhooks.
What can the result protect in a financial web product?
Use scored identifications and account takeover detection at signup and sensitive account access. ShieldLabs does not perform KYC, card verification or transaction authorization.
What are digital footprint checks in fraud prevention?
Digital footprint checks identify device, browser and network risk around online visits. ShieldLabs returns named automation, masking and spoofing detections with identity context and identification risk assessments.
How can digital footprint signals help detect risk before KYC?
ShieldLabs detects bots, multi-accounting and masking at web registration. Named signals and identification risk assessments can support your existing onboarding and identity-verification workflow through API integrations.
Can ShieldLabs help protect browser-based OTP requests?
Yes. ShieldLabs detects bots and multi-accounting around signup and verification requests. Add ready-made risk assessments to your existing verification flow to help prevent automated requests from consuming SMS spend.
Where can ShieldLabs fit in banking or BNPL web flows?
Use ShieldLabs at web signup, sign-in and sensitive account actions. Bot, multi-accounting and account takeover detections help protect onboarding, account access and payment workflows.