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Customer onboarding, screening and ongoing monitoring in one system, with real-time KYC and KYB alerts when a customer's risk changes.

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One-to-one identity, document and data checks against the DVS and Australian data sources, run from the Portal or by API.

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Customers verify their own identity and biometrics from a link on their phone. The result comes back to you, and they keep control of their data.

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Verifies, corrects and enriches customer records so they stay accurate — one at a time or across your whole database.

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The official national death data source. Match your records against it to find and remove deceased individuals.

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Build targeted, privacy-compliant Australian marketing lists with smart filters. Pay only for the records you download.

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Confirm a person or business is who they claim to be: government IDs, biometrics, business registries and employment checks against authoritative Australian sources.

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Meet AUSTRAC obligations and understand customer risk: screening, risk assessment, fraud controls and investigation tools with evidence recorded for each check.

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Keep customer records accurate and put them to work: correct and enrich existing data, unify it into a single view, or build compliant marketing lists from opted-in records.

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Obligations under the AML/CTF Act, from screening at onboarding through to ongoing monitoring — with the evidence for each check recorded.

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Verifying who a customer, employee or account holder is — at sign-up and during ongoing checks — against authoritative Australian sources.

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Keeping customer records accurate, current and complete: validate contact detail, fill the gaps, locate people and remove deceased records.

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Solution datasheet

Social Media Intelligence

Start from a phone number, email address or profile URL and see the accounts linked to it across 28 networks: who they claim to be, where they've worked, and whether the identities agree.

Social & employment
980M+ records
Networks
28 covered
Match
Confidence graded
Use
Verification & screening only

Why a social footprint is worth checking

A real person accumulates accounts over years. A fabricated one has to build them on demand.
verified_user

Identity corroboration

An aged, consistent footprint supports a claimed identity where documents aren't available.

report

Fake profile detection

No linked accounts, or accounts created last month, is a signal worth escalating.

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EDD input

Employment history and public associations feed enhanced due diligence on higher-risk customers.

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Employment screening input

Public profiles corroborate the work history a candidate claims, within your screening policy.

API endpoints

Request schemas and example calls are in the API reference. Sandbox available for integration testing.
helpFAQ

Common questions

Something not covered? Ask our team.

Which networks are covered?

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28 networks, spanning the major social, professional and messaging platforms, across a corpus of more than 980 million social and employment records.

Coverage is strongest where profiles are public by default, which is a real limitation worth stating plainly. A subject who keeps everything private, or who uses platforms built around private accounts, will produce a thinner footprint, and a thin footprint is not by itself evidence of anything.

Is searching by phone different from searching by email or profile URL?

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The starting point differs; the output does not.

Phone and email lookups find the accounts registered to that contact point. You start with a way of reaching someone and end with the identities attached to it.

A URL lookup starts from a profile you already have and expands outward to linked accounts, which is the useful direction when you know who someone claims to be and want to test whether the rest of their footprint agrees.

All three return the same profile structure, so a workflow does not have to branch depending on which identifier you happened to start with.

What does a social footprint tell you that documents cannot?

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Time. A document proves a credential exists; a footprint shows whether an identity has a past.

A real person accumulates accounts over years, on different platforms, for different reasons, with the inconsistencies that naturally follow. A fabricated identity has to build that on demand, and the result usually looks too new, too sparse, or too internally consistent.

This is why social intelligence corroborates a claimed identity in situations where documents are unavailable or where the document checks have already passed and the question is whether the person behind them is real.

How does this help detect fake or synthetic identities?

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The signal is usually absence, not contradiction.

No linked accounts at all, or accounts that were all created within the last month, is a pattern worth escalating, particularly when the applicant's claimed age and circumstances would normally imply a longer trail.

Where accounts do exist, the useful test is whether the identities agree with each other: the same name, a consistent employment history, a plausible location. Fabricated identities tend to be internally consistent within a single profile and inconsistent across several, because each was built to satisfy a different check.

None of this is conclusive on its own. It is an input to a review, not a verdict.

How is confidence graded?

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Each result is graded on how many independent signals agree: name, photo, location and registration data.

A match supported by several converging signals is a materially different finding from a name-only match, particularly for common names, where a name-only match across 28 networks will return a great many people who are not your subject.

Weak matches are flagged as low confidence, not hidden. Suppressing them would be tidier and considerably more dangerous, because it would present a filtered result set as though it were the complete picture.

Can this data be used for marketing?

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No. Social records are licensed for verification and screening purposes only, and marketing use is excluded by contract.

This is a hard boundary, not a policy preference. The licensing that makes this depth of data available for identity and screening work is conditional on it not being repurposed for contact or targeting, and use is subject to that restriction regardless of what your own privacy policy might otherwise permit.

How should findings be used in a screening decision?

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As corroboration and as an input to review, within a written policy that defines scope before anyone runs a check.

For enhanced due diligence, employment history and public associations feed a higher-risk customer review alongside court records and adverse media. For employment screening, public profiles corroborate the work history a candidate has claimed.

The policy matters in both cases, because public profiles surface a large amount of information that is irrelevant to the decision and some that falls into protected categories. Deciding what is in scope in advance is what keeps the check defensible.

Can we run these lookups from our own workflow?

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Yes, through three endpoint groups:

  • Social Check — linked profiles and history
  • Social Contact Expand — find linked phones and email addresses
  • Caspar — identity search

The same lookups run in the Caspar portal, where linked accounts, employment history and consistency appear in a single view. That tends to suit investigative work better than an API response does.

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