Risk Scoring

Risk That Learns. Scores That Mean Something.

deepidv's adaptive risk engine goes beyond static rules. Machine learning models analyze 200+ signals in real-time to produce risk scores that are dynamic, explainable, and actionable — helping you approve more good customers and catch more fraud.

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200+

Signals

Analyzed per verification

<1s

Scoring

Real-time risk decisions

40%

Fewer FPs

vs. rule-based systems

SOC 2

Certified

Enterprise-grade security

Why Risk Teams Choose deepidv

Risk Scoring That Actually Works

N° 01

Multi-Dimensional Signals

Analyze 200+ risk signals from document, biometric, and behavioral data
Device fingerprinting, geolocation, and velocity checks
Cross-reference against fraud databases and watchlists

N° 02

Machine Learning Models

Adaptive models that learn from your verification outcomes
Ensemble scoring combining multiple specialized models
Continuous model retraining on new fraud patterns

N° 03

Explainable Scores

Every score includes detailed reasoning and contributing factors
Human-readable explanations for compliance and audit teams
Drill-down into individual signal contributions

N° 04

Configurable Thresholds

Set approval, review, and rejection thresholds per use case
Dynamic threshold adjustment based on portfolio performance
A/B test different threshold configurations

N° 05

Real-Time & Batch Scoring

Sub-second risk scores for real-time verification decisions
Batch scoring for portfolio review and re-evaluation
Webhook delivery for asynchronous scoring workflows

Use Cases

Real Solutions for Real Risk Challenges

From onboarding to ongoing monitoring, deepidv risk scoring helps you make better decisions at every touchpoint.

1 / 0

Onboarding Risk Assessment

Score every new customer at onboarding with a comprehensive risk assessment. Auto-approve low-risk users, route medium-risk to enhanced verification, and flag high-risk for manual review.

Transaction Monitoring

Apply risk scoring to transactions in real-time. Detect anomalous patterns, flag suspicious activity, and trigger verification workflows when risk thresholds are exceeded.

Synthetic Identity Detection

Specialized scoring models trained to detect synthetic identities — fabricated personas that combine real and fake information to bypass traditional verification checks.

Account Takeover Prevention

Behavioral risk scoring detects when a legitimate account is being used by someone other than the verified owner. Device, location, and behavioral signals combine for accurate detection.

Portfolio Risk Review

Batch-score your existing customer portfolio to identify previously undetected risk. Prioritize re-verification efforts based on risk scores and flag accounts requiring immediate attention.

Fraud Ring Detection

Network analysis models identify connected fraud attempts by detecting shared devices, addresses, documents, and behavioral patterns across your customer base.

Built for Smarter Risk Decisions

Static rule-based scoring misses adaptive fraudsters and blocks good customers. deepidv's ML-powered scoring learns and improves with every verification.

200+ risk signals analyzed per verification
Machine learning models that adapt to new fraud patterns
Explainable scores with full signal attribution
Configurable thresholds per use case and risk appetite
Sub-second scoring for real-time decisions
40% fewer false positives compared to rule-based systems

Trusted & Certified

SOC 2 Type II

Audited security controls for data protection

GDPR Compliant

Full compliance with EU data privacy regulations

ISO 27001

International standard for information security

DIACC Member

Digital ID & Authentication Council of Canada

One API. Full Coverage.

A single RESTful API covers identity verification, AML screening, fraud detection, and continuous monitoring. Go from first call to production in days — not months.

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verify-identity.sh

curl -X POST https://api.deepidv.com/v1/sessions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "type": "identity-verification",
    "checks": [
      "document-verification",
      "face-liveness",
      "aml-screening"
    ],
    "redirect_url": "https://yourapp.com/done",
    "webhook_url": "https://yourapp.com/webhooks"
  }'

# Response:
# {
#   "session_id": "ses_8f2k...",
#   "session_url": "https://verify.deepidv.com/ses_8f2k..."
# }

Verification Sessions

Create hosted verification flows your users complete via link or embed. No frontend code required — just redirect and receive results via webhook.

AML & Screening

Screen against global sanctions lists, PEP databases, and adverse media in a single API call. Ongoing monitoring available for continuous compliance.

Real-Time Webhooks

Get instant notifications when verifications complete, risk scores change, or monitoring alerts fire. No polling required.

Admin Console

Full visibility into every verification — status, audit trails, risk signals, and compliance reporting. Manage API keys, top up tokens, and configure workflows.

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Ready for risk scores that mean something?

See how deepidv's adaptive ML-powered risk engine catches more fraud and approves more good customers.

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Frequently asked questions

Common questions about deepidv risk scoring.

Rule-based systems use static if/then logic that fraudsters quickly learn to bypass. deepidv's ML-powered scoring analyzes 200+ signals simultaneously, detects non-obvious patterns, and adapts to new fraud techniques without manual rule updates. The result is 40% fewer false positives and higher fraud detection rates.

Yes. You can configure approval, review, and rejection thresholds per use case, customer segment, or geography. Thresholds can be adjusted dynamically based on portfolio performance, and you can A/B test different configurations to optimize the balance between conversion and fraud prevention.

Yes. Every deepidv risk score includes a detailed explanation of contributing factors, signal weights, and reasoning. This makes scores auditable and explainable for regulatory compliance, internal audit, and customer dispute resolution. Explanations are available in both human-readable and machine-readable formats.

deepidv's scoring models are continuously retrained on verified outcomes — when you mark a verification as confirmed fraud or confirmed legitimate, the model learns and improves. Models are retrained regularly with your feedback loop data, and new global fraud pattern intelligence is incorporated automatically.

Yes. Risk scores are generated as part of any deepidv verification workflow and are available via API response, webhook, or dashboard. You can use scores to trigger conditional workflow branches, route cases to review queues, or feed into your own risk management systems.

Still have questions?

Our team is ready to help you get started.

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Risk That Learns. Scores That Mean Something.