Sift
Digital commerce fraud platform
Sift focuses on digital fraud decisions. Payment Protection assesses purchases and related abuse; Account Defense addresses account takeover; dispute tools support chargeback operations. It is a fraud layer that can complement an AML and identity stack, rather than a substitute for those controls.
Our assessment
Focused digital fraud specialist. Pair with identity, screening, and AML tools as needed.
Best fit and limitations
A relevant candidate for digital merchants and platforms with card fraud, account takeover, abuse, and dispute workflows. Compare fraud capture and conversion at the same loss target.
- Not established as a sanctions, KYC/KYB, AML monitoring, or regulatory filing suite.
- Dispute tools do not transfer fraud liability unless a specific contract says so.
- Strong consumer fraud detection does not establish business underwriting or merchant reserve management.
Tools 5
Payment ProtectionPurchase and payment fraud+
- Detect stolen cards, card testing, and related abuse
- Use scores, workflows, and manual-review context
Account DefenseAccount takeover controls+
- Assess device, behavior, velocity, and session risk
- Inform allow, challenge, and stronger intervention decisions
Score Explainability + network viewsAnalyst investigation+
- Inspect reasons behind risk decisions
- Review transaction activity and connected behavior
Workflow simulationPolicy testing+
- Test risk policy changes before deployment
- Tune thresholds and review workflows
Dispute ManagementChargeback operations+
- Support dispute handling and outcome analysis
- Confirm current availability and integrations
AI capabilities
Ensemble fraud models + review summaries
Sift applies AI/ML to network and customer events. ActivityIQ in Account Defense provides generative summaries of cross-session behavior. This is review assistance; independent case or filing authority is not established.
What to validate
Evaluate chargeback-lag effects, score reasons, policy simulation, and account-recovery outcomes. A low score is not a compliance clearance.
Implementation
Integration checklist
- Send complete lifecycle events, including account, session, order, and payment context.
- Return fraud and dispute outcomes with consistent labels and timestamps.
- Define allow, challenge, review, and block actions in the product and payment stack.
Commercial scope
Quote required. Separate payment events, account protection, dispute tools, analyst access, and support.
Questions for the demo
- What is the approval-rate lift at a fixed fraud-loss target?
- How do delayed chargebacks affect model feedback and our backtest?
- Which account and payment actions are automatic versus API recommendations?
Engineering
- Inputs
- Lifecycle events keyed to a user identifier and JavaScript activity · Login and account events, device signals, and session behavior
- Outputs
- Product-specific risk scores and workflow status · Session-risk context and allow, challenge, block, or review actions
- Webhooks
- Decision webhooks deliver configured workflow decisions. Consult the selected API version for authentication and delivery behavior.
- Decision timing
- An event request can return a score or score plus workflow status synchronously; scores can also be retrieved separately.
- Deployment
- Deployment options not verified.
- Dependencies
- Events or JavaScript activity for the referenced user · Enabled abuse-detection products · Integration with the customer's authentication or orchestration flow
Verified details 9
- Inputs
Lifecycle events keyed to a user identifier and JavaScript activity
Source Checked 2026-09-18 - Outputs
Product-specific risk scores and workflow status
Source Checked 2026-09-18 - Webhooks
Decision webhooks deliver configured workflow decisions. Consult the selected API version for authentication and delivery behavior.
Source Checked 2026-09-18 - Decision timing
An event request can return a score or score plus workflow status synchronously; scores can also be retrieved separately.
Source Checked 2026-09-18 - Dependency
Events or JavaScript activity for the referenced user
Source Checked 2026-09-18 - Dependency
Enabled abuse-detection products
Source Checked 2026-09-18 - Inputs
Login and account events, device signals, and session behavior
Source Checked 2026-09-18 - Outputs
Session-risk context and allow, challenge, block, or review actions
Source Checked 2026-09-18 - Dependency
Integration with the customer's authentication or orchestration flow
Source Checked 2026-09-18
Vendor example
Published vendor example. Confirm the current version and required credentials.
{
"decision_id": "block_user_payment_abuse",
"source": "MANUAL_REVIEW",
"analyst": "analyst@example.com",
"description": "User linked to three other payment abusers and ordering high value items"
}Integration limits
- Published vendor payload example, linked to its source. It is not a complete integration or a tested production request.
- Empty country, deployment, or provider lists mean not verified in this review. A documented country refers to the specific product noted in its source, not universal platform coverage.
- A model score is a fraud signal, not a sanctions or compliance clearance. Client applications remain responsible for downstream enforcement.
- The vendor example is the published Apply Decisions user request body. It records a configured decision; it does not execute a payment block in your application. It was not executed.
- Session controls can target a suspicious session without locking the entire account. ActivityIQ summarizes activity; it does not establish independent compliance clearance.
Sources 3
Source review dates are shown above. Product claims come from public sources. Fit, limits, and evaluation questions are our analysis. This is not a hands-on performance test. Methodology · Changelog