Fraud detection APIs: 7 platforms compared

The short version

Fraud platforms identify events that need scrutiny. Transaction-time identity verification adds evidence that the expected person is present. The right stack depends on whether the workflow needs risk decisioning, identity evidence, or both.

• Fraud platforms determine when an account, user, or transaction needs scrutiny.
• Transaction-time identity verification provides evidence about whether the expected person is present.
• Sardine suits financial-crime programs that need risk decisions, alerts, case management, and step-up workflows.
• Sift suits digital commerce products that need account takeover prevention and transaction decisioning.
• Alloy suits banks and fintech products that need identity and fraud orchestration across the customer lifecycle.
• SEON suits developers seeking a modular fraud detection API with scores, reasons, rules, and native identity verification.
• Stripe Radar suits businesses that want payment-risk controls inside Stripe.
• Fraud.net suits enterprises seeking fraud monitoring, entity risk analysis, and investigation capabilities.
• Stile complements these platforms when a flagged event requires document, face-match, liveness, or supported mobile driver's license verification and a signed result.
• Vendors charge for different units, so transaction screening, platform access, case operations, and identity checks require separate cost comparisons.

What is fraud risk scoring?

Fraud risk scoring estimates how likely an account, user, or transaction is fraudulent using behavioral, device, payment, and network signals. Fraud detection software combines inputs such as device fingerprints, IP location, transaction velocity, purchase amount, and historical behavior to produce a numerical probability. A fraud detection API can return that score in milliseconds, along with reasons or recommended actions.

The score measures how closely an event resembles known legitimate or fraudulent patterns. For example, a rapid high-value purchase from a new device or unusual location may raise the score. A customer policy can then approve the event, request another check, send it for review, or block it. Each company sets exact thresholds based on its risk tolerance, and illustrative scoring bands often reserve step-up checks for uncertain cases.

A risk score alone does not prove the expected person is present. Transaction-time identity verification can provide stronger evidence that the expected person is present during the flagged event. Visa's fraud detection guide describes risk scoring and identity verification as distinct parts of fraud detection.

Scope and selection criteria

Stile publishes this guide, and we include our own product as a complementary transaction-time identity layer rather than as a ranked fraud-scoring competitor. The evaluation prioritizes first-party product documentation and published pricing where available. We last reviewed the information on August 15, 2026.

The selected products represent distinct roles in financial-crime operations, digital-commerce protection, identity orchestration, modular fraud screening, payment risk, and transaction-time identity verification. Each product has a distinct scope and output, with different integration and identity-check options.

Stile: the complementary identity layer

Stile is not a fraud-scoring platform and is not ranked against the six above. It provides transaction-time identity verification infrastructure: the API evaluates event-bound document evidence, face matching, facial liveness, and supported mobile driver's licenses, then returns a signed result to the customer's workflow. The customer combines that result with its fraud signals and applies its own allow, hold, or deny policy.

Strengths

• Developers can request stronger identity evidence only after an existing fraud system or policy flags an event.
• The signed result gives the application a separate identity signal without requiring Stile to operate the surrounding risk engine.
• Raw source images and biometric captures are processed during verification and deleted at completion by default.

Trade-offs

• Stile does not perform transaction monitoring, behavioral risk scoring, case management, or chargeback operations.
• Customers must supply the trigger logic and connect the result to their own decision policy.
• Teams whose existing platform already provides suitable event-time verification may not need another identity layer.

Pricing

Stile charges $0.38 per full check with 100 free checks per month and volume tiers, published on the pricing page. Because customers pay for identity checks rather than screened transactions or managed fraud operations, this billing unit is not directly comparable with fraud-platform pricing.

Set risk thresholds before requesting identity proof

Map risk bands to approval, challenge, review, or blocking before production traffic is evaluated. Fraudio's fraud risk scoring guide describes the score as a real-time measure of risk for a transaction, account, or entity.

Risk bands help customers choose an appropriate response. In Fraudio's illustrative 0-to-1 model, scores below 0.3 receive automatic approval, scores between 0.3 and 0.7 trigger a challenge, and scores above 0.7 trigger a block, although each customer sets thresholds according to its own risk tolerance. Visa's fraud detection guide similarly describes adaptive scoring that requests step-up authentication when risk warrants further scrutiny.

Identity proof becomes useful when an event carries meaningful consequences and unusual signals cannot establish who is acting. A high-value purchase from a new country may justify a challenge, especially when the account also uses an unfamiliar device. Rapid transactions or other velocity spikes can provide another trigger. Microblink's transaction risk scoring guide identifies document verification and biometric authentication as possible step-up measures for higher-risk events.

Verification triggers should account for both the strength of the anomaly and the consequence of an incorrect approval. That prevents a low-impact anomaly from receiving the same treatment as a consequential event such as a payout or account recovery. The customer then combines the identity result with its fraud signals and policy rules to allow, hold, or deny the event.

How fraud scoring and identity verification work together

Fraud and identity systems pass control through a defined five-step sequence.

1. The fraud system produces a risk signal from behavioral, device, payment, or network evidence.
1. The customer's policy compares that signal with thresholds for the specific event.
1. The application launches an identity challenge when the policy requires stronger evidence.
1. The identity provider returns a result indicating whether the person passed the requested checks.
1. The customer combines that result with its risk signals and decides whether to allow, hold, or deny the action.

A threshold-based trigger limits identity friction to events that warrant closer scrutiny. A new device and an unusual purchase amount could raise a score enough to request verification rather than immediately block the payment. Risk scores commonly map to approval, step-up, review, or blocking actions, but each customer sets thresholds according to its risk tolerance and the consequences of the event.

With Stile, the application invokes a document, face-match, liveness, or supported mobile driver's license check after its fraud system triggers the policy. Stile evaluates the requested identity evidence and returns a signed result. Stile does not determine the original risk score and does not make the final decision for the customer.

By default, Stile deletes raw source images and biometric captures when verification completes, and retains signed outcomes and audit metadata. Stile may also retain one-way hashed anchors for deduplication or returning-user checks.

Where Stile fits in the stack

Consider Stile when a risk workflow needs event-bound identity evidence that existing controls do not provide.

Consider Stile when

• A consequential action, such as an account recovery or payout, requires proof that the expected person is present.
• The policy engine needs a separate signed identity result before making a decision.
• Existing authentication or fraud scoring can flag an event but cannot supply the required document, face-match, liveness, or supported mDL evidence.
• The data policy favors transient processing. Stile deletes raw source images and biometric captures after completion by default, while retaining signed outcomes and required audit metadata.

Do not add another identity layer when

• A platform's native verification or orchestrated IDV provider already supplies the required evidence and retention model in covered markets.
• The actual gap concerns transaction monitoring or behavioral risk scoring. Stile does not perform either function.
• The application needs chargeback operations or case management rather than identity proof. Fraud platforms address those operational needs.

Choose by your main constraint

• Use Sardine for broad fraud, AML, and case operations.
• Use Sift for account takeover prevention and digital commerce decisioning.
• Use Alloy for vendor-neutral bank and fintech orchestration.
• Use SEON for a modular fraud API with native identity verification.
• Use Stripe Radar for payment risk within Stripe.
• Use Fraud.net for enterprise monitoring and investigation.
• Add Stile when a risk trigger requires confirmation that the expected person is present.

When to combine fraud scoring and identity verification

Fraud scoring platforms fit workflows that need continuous monitoring, risk decisions, rules, case management, or payment controls. Transaction-time identity verification fits narrower moments when a consequential action requires stronger evidence that the expected person is present.

Add identity verification when its evidence can change the decision. Existing native or orchestrated verification may already cover that need. Use both systems only when the event's risk and consequences justify the added friction.

Methodology

Stile publishes this guide, and we present our own product as a complementary identity layer rather than a ranked fraud-scoring vendor. The comparison covers distinct product roles in payment risk, account protection, orchestration, and financial-crime workflows.

The research favored first-party vendor sources, and independent sources supported comparative claims only where vendor materials could not. We last reviewed pricing on August 15, 2026. Where a vendor does not publish pricing, the comparison labels it not disclosed. Where a vendor's documentation does not describe a capability, the comparison says so rather than asserting the capability is absent.

Product scope and commercial terms change. Before choosing a platform, verify each vendor's current prices, APIs, service commitments, retention terms, and enabled markets. Buyers should test score outputs and examine how review actions and step-up checks behave with their own traffic and risk policies.