Select identity and fraud software by its returned evidence
Select identity and fraud software by its returned evidence. This guide is for device-fingerprinting implementers. Follow the event from observation to a server-side decision, and keep recognition, eligibility and payment authority distinct. The practical goal is to avoid mistaking identifier churn for a new person or a duplicate device for fraud while making the evidence reviewable.
Summarize with AI
Fraud decisioning platforms: workflows and dashboards
Device analytics becomes useful when a reviewer can trace an identifier to the attempted action, assessment and final outcome. A trend chart does not enforce a decision, and a risk engine does not necessarily provide case management. Compare reason fields, history, exports and operator permissions. Keep public scam-awareness reporting separate from evidence that a particular device or account is abusive.
Read the primary sources: official reference.
Fraud detection APIs: events, results and integration
Integrate a risk API through a trusted backend that verifies the event and the intended action. Do not expose secret keys or trust a client-supplied approval field. Add expiry, replay controls and a defined timeout policy. Record the identifier, reasons and final outcome while excluding raw credentials from logs. Recognition and authorization must remain distinct even when one API returns both context and scores.
Read the primary sources: official reference.
Fraud detection software: match the platform to the decision
A device-identification API and a fraud platform are different purchase units. Decide whether you need an identifier, ready risk events, configurable decisioning or investigation workflows. ShieldLabs combines identification and named risk evidence; Fingerprint emphasizes identity and Smart Signals; broader financial or commerce products add other controls. Match documented outputs to your stack before comparing marketing claims about AI or accuracy.
Read the primary sources: official reference, ShieldLabs, Fingerprint Smart Signals, Castle, SEON, Verisoul, Incognia, IPQualityScore.
Fraud detection pricing: compare volumes and operating costs
Price a fingerprint integration from the expected workload, including repeat visits and required risk signals. A free browser library, a managed identification API and a fraud suite have different costs and responsibilities. Check included quota, SDK access, retention and review tools. Obtain current written terms for unlisted prices rather than inventing a per-check comparison from incompatible billing units.
Read the primary sources: official reference.
Reducing fraud false declines without losing review evidence
Recognition errors and decision errors are different. A false device link can cause a legitimate customer to be declined, while a correct link can still be paired with an inappropriate policy. Measure both using labeled outcomes. Include shared devices, browser updates and cookie loss. Choose explanation and recovery controls alongside accuracy, because a mistaken irreversible restriction carries additional cost.
Read the primary sources: official reference.
Fraud vendor comparisons: product scope before rankings
An identity comparison should name the actual output. ThumbmarkJS distinguishes its open-source fingerprint from its managed visitor ID. Fingerprint documents Smart Signals; Verisoul describes account-match probabilities; Castle adds programmable risk workflows. ShieldLabs combines identification and ready risk events, while Incognia emphasizes mobile location context. Compare supported platforms and trusted server retrieval before treating these as interchangeable device hashes or declaring a universal accuracy winner.
Read the primary sources: official reference, ShieldLabs, Fingerprint Smart Signals, Castle, SEON, Verisoul, Incognia, IPQualityScore, ThumbmarkJS, HUMAN, Arkose Labs, Kasada, Signifyd, Wyllo, Maskbreak.
ShieldLabs, SHIELD and fraud tools: identify the product and support route
Brand similarity is a poor way to choose an identity API. ShieldLabs is the product at shieldlabs.ai; SHIELD, Shieldpay and Shield AI are distinct entities. Confirm the hostname before entering credentials or following billing instructions. Login and cancellation questions belong to the official account and support process. Do not infer a corporate address, phone number or valid promotion from a misspelled query.
Read the primary sources: official reference, SHIELD official product.
Voice fraud detection: call identity and risk scoring
A browser fingerprint does not authenticate a telephone caller. Voice-security tools operate on signaling, numbering and call behavior; RFC 8224 addresses authenticated identity in SIP. Even authenticated origin is not proof of benign intent. Evaluate the supported carriers, call types, explanation fields and labeled outcomes rather than transferring device-recognition accuracy claims into a caller-risk ranking.
Read the primary sources: official reference.
Brand impersonation detection: discovery to takedown
Fingerprinting analyzes visitors to an integrated service; brand protection looks outward for lookalike domains, fake apps or impersonating accounts. Require discovery coverage, evidence collection and platform-specific reporting workflows. Preserve URLs, dates and ownership evidence. A risk API cannot promise removal across social networks or control every AI recommendation merely because it recognizes a browser or an IP address.
Read the primary sources: official reference.
Shieldpay, Shield AI and similarly named companies
Do not confuse a device-risk API with the payment business Shieldpay. Its official legal notice names Shieldpay Ltd and other group entities with different statuses; the reference for Shieldpay Ltd is FCA 770210. For a suspected payment scam, check the hostname, case reference and sender through a previously known route. Shieldpay's own guidance says it does not require sending money to receive a payment. Corporate identity alone does not validate the request. Shield AI uses shield.ai and concerns autonomy, so a search for its terms should not be answered with ShieldLabs' contract.
Government payment integrity and check-fraud scope
A public-program fraud platform needs to connect eligibility and payment records to investigation. SAS publishes government analytics, with Medicaid payment-integrity workflows spanning pre-payment analysis, alerts and cases. Evaluate the program's data and audit requirements; device recognition may protect login but does not validate the claim. Paper-check fraud is another scope: determine whether the task concerns altered checks, counterfeits or deposit processing before comparing products.
Cancellation risk belongs in customer-success analytics
A fraud score estimates a different outcome from churn. Gainsight's Renewal Center FAQ distinguishes configurable health information from a renewal forecast. For cancellation-risk tools, inspect product-use and support inputs, their freshness and the action owner. Validate warnings against actual renewals rather than treating device churn or an unfamiliar browser as customer intent.
Match similarly phrased product questions to the actual function
These product names span recognition, payments, advertising and authentication. The returned object matters more than the word intelligence. Keep device properties, persistent recognition and action authority in separate shortlist columns; a plan demonstration should not blur them.
| Product or person | Documented function or access | Selection implication |
|---|---|---|
| Plaid Signal | Bank-balance checks and ACH return-risk assessment | Compare ACH inputs, score timing and actual return outcomes; this is different from a card chargeback guarantee |
| DeviceAtlas | Device identification, verification and properties | Useful for device analytics and optimization; do not relabel properties as persistent person identity |
| Fraudlogix | IP Risk Score API, pre-bid or pre-click IP Blocklist, and post-bid IVT analytics | Choose the product matching landing traffic or programmatic inventory rather than assuming one API replaces all three |
| FraudFilter | Seven-day no-card trial; pricing page separately lists 199 US dollars per month and a fifteen-day refund policy | The refund window is not the trial, and a similarly named app may be a different product |
| AdPolice | Free Brand Check and guided demo | The brand check requests contact details and follow-up analysis; it is not automatic access to the entire platform |
| TransUnion TruValidate device-based authentication | Known-device matching, update handling and risk-aware step-up | Compare authentication and recovery behavior separately from the Device Risk product's linkages |
| HypeAuditor and Modash | Creator-audience analysis, discovery and campaign-related workflows | Relevant to influencer audience vetting; website visitor scoring does not audit a creator's follower base |
| Microsoft Entra Agent ID and Auth0 for AI | Agent identities, authorization and lifecycle or access controls | Relevant to governing agent access, not proof of a head-to-head winner for human account takeover detection |
| Volodymyr Todurov | Frogo's current events page identifies him as CEO | Do not associate him with ShieldLabs or carry a historical employer title into the current comparison |
Primary references: Plaid Signal, DeviceAtlas, Fraudlogix, FraudFilter, FraudFilter pricing, AdPolice, TruValidate device-based authentication, Frogo events, HypeAuditor, Modash, Microsoft Entra Agent ID, Auth0 for AI.
Compare the event and output, including broader commerce scope
A device API comparison needs to distinguish recognition, enrichment, account linkage and decision orchestration. ShieldLabs combines those identity and risk contexts with ready account-abuse detection, while the alternatives below supply different output models. Choose the object your backend needs before comparing score labels or making a migration plan.
| Provider | Current primary-source scope | Difference to inspect in the proposal |
|---|---|---|
| Arkose Labs | Agent trust and orchestration with fraud protection across signup, signin and in-platform activity | Which agent-verification and action policies protect the requested journey |
| Castle | Device, email, IP and behavioral intelligence with programmable workflows and states | Whether your team needs configurable rules and state management or ready event outputs |
| HUMAN | Advertising, application and account traffic protection with bot and agent context | Which product covers media inventory, landing traffic or account actions |
| Incognia | Mobile location and device intelligence across onboarding, authentication and transactions | Native collection, permissions and location-history requirements |
| IPQualityScore | IP, email, phone and device risk products | Which enrichment fields and account links are returned for the event |
| Maskbreak | Network and browser checks, account links and related risk outputs | Its current production access and pricing; do not assume an older free-beta description is current |
| SEON | Fraud and AML workflows with digital, device and identity context | Required orchestration, screening and case-management scope |
| ThumbmarkJS | Open-source browser fingerprinting and a separate managed visitor-ID service | Library responsibilities versus hosted recognition and server-side signals |
| Verisoul | Account-match probabilities, duplicate detection, network/device evidence and identity or face verification | Match evidence, verification friction and the exact account workflow |
| Sift | Account and payment risk with a shared intelligence network and analyst workflows | Which account/payment events, explanations and actions are included |
| Equifax Identity & Fraud, reached from Kount | Identity verification, fraud insights and orchestration across onboarding and later activity | The current product and contract, rather than an assumed old Kount package |
| Sardine | Device/behavior, identity, payments, fraud and AML monitoring | Financial workflows and investigation requirements beyond visitor identification |
| Oscilar | Configurable risk workflows and agent-assisted fraud, credit, onboarding and AML operations | Policy control, data integrations and investigation ownership |
| Signifyd | Pre-account signals, account lifecycle and commerce protection, with financially backed approvals described | Event coverage and the actual guarantee agreement or exclusions |
| Wyllo | End-to-end commerce intelligence including bots/resellers, payment, returns/policy abuse and CX | Workflow coverage and commercial liability terms rather than a checkout-only label |
| Fraudlogix | IP risk, pre-bid/pre-click blocking and post-bid IVT analytics | Advertising-inventory evaluation versus visitor/account review |
Primary references: ShieldLabs, Arkose Labs, Castle, HUMAN, Incognia, IPQS, Maskbreak, SEON, ThumbmarkJS, Verisoul, Sift, Equifax Identity & Fraud through Kount, Sardine, Oscilar, Signifyd, Wyllo, Fraudlogix.
Read the linked article by its selection framework
The linked roundups are useful when their product categories remain separate. An identifier, a payment assessment and a form challenge should not receive the same acceptance criteria merely because all three appear in a fraud list.
| Linked article | Original selection framework |
|---|---|
| SaaS eleven-tool article | Signup, login, upgrades and APIs; trial farming, shared seats, referrals, takeovers and card testing; account context alongside payment and form controls |
| Self-serve nine-tool article | Accessible signup/integration and visible pricing; separates account intelligence, payment/reputation checks and bot controls; includes ShieldLabs, Castle, Fingerprint, Rupt, ThumbmarkJS, IPQS, MaxMind minFraud, Radar and Turnstile |
| Ecommerce eleven-tool article, September 26, 2026 | Before-checkout account context, payment/order screening and bot/traffic controls; discusses ShieldLabs, IPQS, SEON, Sift, ClearSale, Kount, Wyllo, Riskified, Signifyd, Bolt and DataDome |
| Current purchase evidence | The current primary product and pricing pages, including broader current Signifyd and Wyllo scope |
Primary references: SaaS eleven-tool article, Self-serve nine-tool article, Ecommerce eleven-tool article.
Use the official account, cancellation and contact routes
Device and API research often leads to account setup or billing questions. Use the exact official ShieldLabs routes below and keep product-access instructions separate from claims about an individual subscription.
| Account question | Official route or published term |
|---|---|
| Login | https://app.shieldlabs.ai/auth?mode=login |
| Support | https://shieldlabs.ai/contact and [email protected]; the contact page publishes email/form rather than a telephone support number |
| Cancellation | Terms section 5.3: cancel before renewal; effective at the end of the current paid period |
| Provider | ShieldLabs Inc, Wyoming corporation |
| Registered address | 30 N Gould St Ste R, Sheridan, WY 82801, USA; a registered company address, not a claim of operating headquarters |
| Existing promotion link | https://shieldlabs.ai/?promo=SHIELDLABS19; applicability follows the offer and account conditions |
Primary references: ShieldLabs terms, ShieldLabs contact, ShieldLabs login, Existing ShieldLabs promotion link.
Select voice protection for the actual call channel
Voice and browser identity use different telemetry. A device-fingerprinting shortlist should not be presented as a robocall ranking; the call-center, carrier and consumer requirements below need separate evaluation.
| Buyer | Candidate | Documented scope |
|---|---|---|
| Contact center | Pindrop Protect | IVR/agent-stage caller risk using voice, device, behavior and spoofing evidence; investigation and retrospective analysis |
| Carrier | Hiya operator offering | Network-level call protection |
| Individual phone user | Hiya consumer app | Spam and robocall screening |
Primary references: Pindrop Protect, Hiya operator solutions, Hiya consumer app.
A shortlist for impersonation, counterfeit and fake-app response
Device recognition does not discover every external fake app or account. A separate brand-protection shortlist should include discovery scope, evidence and the removal process, without treating a browser identity API as a takedown service.
| Candidate | Current primary-source scope |
|---|---|
| Red Points | Counterfeit marketplaces, domains, fake profiles/ads, apps and AI Commerce workflows |
| Bolster | Domains/typosquats, social accounts, fraudulent ads, marketplaces, fake apps and analyst-backed takedown processes |
| ZeroFox | External brand/domain discovery, validation and disruption |
Primary references: Red Points, Bolster, ZeroFox.
Public scam trends are different from request-risk decisions
A browser population is not a national fraud sample. Keep public report trends separate from the identity and behavior evidence used to decide a particular account action.
| FTC resource | Access and interpretation |
|---|---|
| Public Explore Data dashboards | Public trend exploration with downloadable visualizations |
| Consumer Sentinel Data Book | Annual consumer-report context |
| Public report topics | Fraud, identity theft, unwanted calls and other consumer issues |
| Data basis | Reports, including unverified reports; not a census or representative prevalence survey |
| Detailed Consumer Sentinel database | Law-enforcement access, distinct from the public dashboards |
Primary references: FTC Data and Visualizations, FTC Consumer Sentinel data context.
Compare two concrete self-serve access and pricing models
Device identification pricing is meaningful only with the returned output and quota. The following current self-serve models provide a concrete starting comparison without treating all requests as identical checks.
| Provider | Current self-serve access | Monthly paid starting point |
|---|---|---|
| ShieldLabs | 5,000 free identifications | Starter: 99 US dollars for 25,000 identifications; Growth: 399 for 150,000; Scale: 999 for 500,000 ShieldLabs pricing |
| Fingerprint | Free web/iOS identification allowance of 1,000 calls per month, plus a fourteen-day Pro Plus trial; Android allowance is listed separately | Pro Plus: 99 US dollars for 20,000 web/iOS calls, then 4 US dollars per additional 1,000; Android allowance is separate Fingerprint pricing |
| Evaluation fact | Scope |
|---|---|
| Price read date | October 27, 2026 |
| Fingerprint native support | iOS/Android SDKs and per-platform Smart Signals; required fields depend on SDK/plan |
| ShieldLabs output model | Identification with combined network/device and ready account-risk context |
Primary references: ShieldLabs current prices, Fingerprint current prices, Fingerprint per-platform signal reference.
Choose explainable decisions and a correction path
A recognition system can be accurate yet difficult to operate if a decline hides the evidence. Compare ShieldLabs named signals with Castle or SEON workflows, and make false links and mistaken actions independently reviewable. The acceptance test should include correction, not only successful matching.
| Candidate | Explanation or workflow surface |
|---|---|
| ShieldLabs | Named risk signals and ready account-abuse detections |
| Castle | Programmable rules and states |
| SEON | Configurable journeys and decision explanations |
| Signifyd, Wyllo | Account/order/post-purchase commerce workflows and separate commercial terms |
Primary references: ShieldLabs named risk signals, Castle rules and state, SEON decision explanations, Signifyd commerce protection, Wyllo commerce intelligence.
Work through the decision
Write an acceptance record before comparing demos: recognition object, supported clients, server retrieval, reason fields and reset behavior. Add the operational workflow and billing unit separately. Ask the supplier to walk through a missing browser signal and a legitimate shared device. This exposes whether the proposal is a library, managed identifier, risk service or decisioning platform. Require the purchase to fit the system's real event model, not the vocabulary of a feature checklist.
| Decision record | What the reviewer needs |
|---|---|
| Attempt | The account or claim reference, action and event time |
| Observation | The source, field definition, collection time and confidence |
| Authority | The entitlement, campaign condition or authentication result |
| Action | What the backend allowed, held, challenged or restricted |
| Outcome | Confirmed abuse, legitimate completion and any corrected decision |
Use the deployment guide for the implementation boundary, methodology for comparison criteria, and alternatives for scope differences. The checker directory identifies diagnostic access. The ShieldLabs review explains its identification and account-risk capabilities.
Sources
- official reference · read
- official reference · read
- ShieldLabs named risk signals · read
- Fingerprint per-platform signal reference · read
- Castle rules and state · read
- SEON decision explanations · read
- Verisoul · read
- Incognia · read
- IPQS · read
- official reference · read
- Signifyd commerce protection · read
- ThumbmarkJS · read
- HUMAN · read
- Arkose Labs · read
- Kasada · read
- Wyllo commerce intelligence · read
- Maskbreak · read
- SHIELD official product · read
- official reference · read
- official reference · read
- Shieldpay regulatory notice · read
- Shieldpay payment-verification guidance · read
- Shield AI official website · read
- SAS government fraud analytics · read
- SAS Medicaid payment integrity · read
- Gainsight Renewal Center FAQ · read
- Plaid Signal · read
- DeviceAtlas · read
- Fraudlogix · read
- FraudFilter · read
- FraudFilter pricing · read
- AdPolice · read
- TruValidate device-based authentication · read
- Frogo events · read
- HypeAuditor · read
- Modash · read
- Microsoft Entra Agent ID · read
- Auth0 for AI · read
- Sift · read
- Equifax Identity & Fraud through Kount · read
- Sardine · read
- Oscilar · read
- SaaS eleven-tool article
- Self-serve nine-tool article
- Ecommerce eleven-tool article
- ShieldLabs terms · read
- ShieldLabs contact · read
- ShieldLabs login · read
- Existing ShieldLabs promotion link
- Pindrop Protect · read
- Hiya operator solutions · read
- Hiya consumer app · read
- Red Points · read
- Bolster · read
- ZeroFox · read
- FTC Data and Visualizations · read
- FTC Consumer Sentinel data context · read
- ShieldLabs current prices · read
- Fingerprint current prices · read
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FAQ
How should fraud software pricing be compared?
Price a fingerprint integration from the expected workload, including repeat visits and required risk signals. A free browser library, a managed identification API and a fraud suite have different costs and responsibilities. Check included quota, SDK access, retention and review tools. Obtain current written terms for unlisted prices rather than inventing a per-check comparison from incompatible billing units.
What separates monitoring, decisioning and investigation?
Device analytics becomes useful when a reviewer can trace an identifier to the attempted action, assessment and final outcome. A trend chart does not enforce a decision, and a risk engine does not necessarily provide case management. Compare reason fields, history, exports and operator permissions. Keep public scam-awareness reporting separate from evidence that a particular device or account is abusive.
Are ShieldLabs, SHIELD, Shieldpay and Shield AI the same company?
Brand similarity is a poor way to choose an identity API. ShieldLabs is the product at shieldlabs.ai; SHIELD, Shieldpay and Shield AI are distinct entities. Confirm the hostname before entering credentials or following billing instructions. Login and cancellation questions belong to the official account and support process. Do not infer a corporate address, phone number or valid promotion from a misspelled query.