deepidv AML questionnaires use AI to dynamically generate risk-based questions tailored to each applicant's jurisdiction, entity type, and transaction profile — replacing static forms with adaptive screening that satisfies regulators and catches what checkbox compliance misses.
AI selects questions from the jurisdiction, entity type, and risk signals — and unlocks conditional follow-ups the moment an answer reveals a new risk vector.
Response patterns, timing, and consistency feed a composite 0–100 risk score, flagging evasive or contradictory answers before onboarding completes.
Every question, answer, score, and decision is timestamped into an immutable record — exportable as an examiner-ready report on demand.
By the NumbersDynamic AML questionnaires that adapt to local rules, score risk as they go, and leave a complete trail behind them.
Dynamic GenerationStatic paper forms ask everyone the same questions. deepidv's AI evaluates jurisdiction, entity type, declared activity, and initial risk signals to assemble a questionnaire that fits the applicant — then adapts in real time as answers reveal new risk vectors.
How it adapts
Risk-based selection
Drawn from jurisdiction & entity type
Conditional follow-ups
Unlocked by detected risk patterns
211+ rule sets
Local AML/CTF requirements applied
Always current
Updates when regulations change
Are any directors or shareholders politically exposed?
→ No direct PEP status
Do beneficial owners hold ≥ 25% equity?
Confirm primary transaction jurisdiction
Triggered by: ownership risk vector · answers unlock branches in real time
Behavioral Risk ScoringEvery answer is scored against the expected response for the declared risk profile. deepidv also reads behavioral signals — timing, consistency, and evasion patterns — to produce a single 0–100 risk score that branches your onboarding logic automatically.
Signals analyzed
Answer consistency
Contradictions flagged in real time
Response timing
Hesitation & evasion patterns
Jurisdiction risk
Weighted by local exposure
Composite score
0–100 for downstream decisioning
0–100 composite · route to EDD review
ownership ≥ 25% · jurisdiction flag
Audit-Ready by DefaultEvery question presented, answer given, score computed, and decision made is written to an immutable, timestamped record. Export examiner-ready reports on demand, and drop the whole flow into any onboarding journey through a REST API or embeddable SDK.
Records & integration
Immutable trail
Hash-chained, timestamped entries
Examiner-ready export
PDF/HTML for FATF & local exams
REST API & SDK
Deploys into any onboarding flow
Webhook events
Real-time downstream processing
Built to meet the world's most demanding security and privacy standards.
Audited security controls for data protection
Full compliance with EU data privacy regulations
International standard for information security
Digital ID & Authentication Council of Canada
IntegrationPlug deepidv into your stack three ways — a REST API, native SDKs, or an MCP server your AI agents can call directly. Clean docs, a sandbox, and one source of truth take you from API key to live verification the same day.
Call any verification service directly — create a session or run a standalone check and get structured JSON back in under 500ms.
→ screening 200+ watchlists…✓ status: clear risk_score: 4 · 143msPre-built UI components and server libraries for iOS, Android, Web, Node, Python, and Go — zero to live verification in a single sprint.
checks: ['id','liveness','face'],✓ v.url → send to your userAn open protocol that lets any AI agent call deepidv's verification engine directly — no custom integration code. Connect it in one command.
Changelog
Multi-language verification, a redesigned ID & face-capture flow, end-to-end whitelabel, and a native Background Check step.
Read moreAI background-confirmation calls, faster camera start-up, translated PDF/HTML reports, and location-by-IP enrichment.
Read moreContinuous, AI-driven adverse-media checks built natively into your verification workflows.
Read moreStay AML CompliantSee how deepidv AML questionnaires adapt in real time — it takes 60 seconds.
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