Detect fraud at the point of application — not after settlement. HIDF analyses behavioural signals, financial records, and digital footprints that rule-based systems miss. Fully explainable. Built for AUSTRAC-regulated entities.
INTERPOL's 2026 assessment: $442 billion in global fraud losses, with AI-enhanced schemes 4.5x more profitable than traditional methods.
Most lending fraud is discovered months after settlement when the borrower defaults. The fraudulent loan is already on your books. Recovery is unlikely. Early detection at point of application is the only effective defence.
Synthetic identity document fraud surged 311% between Q1 2024 and Q1 2025 (Experian). Deepfake documentation and AI-generated applications bypass every pattern rule-based systems were built to catch.
Fraud rings iterate in weeks. Legacy vendors update in quarters. That gap is where losses happen — and sophisticated actors know it.
Up to 95% of AML alerts are false positives, each consuming up to 22 hours of investigation time. That is millions in wasted analyst hours — and genuine threats buried in noise.
AUSTRAC suspicious matter reporting obligations require lenders to detect and report lending fraud. Responsible lending under the NCCP Act demands verified income and expenses. APRA prudential standards hold boards accountable for credit risk. Non-compliance is no longer a risk you can absorb.
NICE Actimize, Feedzai, and ComplyAdvantage serve global markets — none are purpose-built for Australia's regulatory environment. HIDF is: AUSTRAC-aligned, APRA CPS 234 ready, designed for the AML/CTF Act, NCCP Act responsible lending obligations, and APRA prudential standards from day one.
Your data already holds the answers. HIDF extracts the behavioural, statistical, and contextual signals that reveal sophisticated fraud — with the explainability Australian regulators require.
AI-powered financial crime prevention that augments your existing stack — built to meet AML/CTF Act, APRA CPS 234, and NCCP Act responsible lending obligations.
Flag high-risk loan applications before approval. Behavioural anomaly detection surfaces threats the moment suspicious patterns emerge — not months after settlement.
Score applicant risk across financial records, digital footprints, and behavioural signals. Every score is explainable, auditable, and regulator-ready.
Transform raw applicant and lending data into structured fraud intelligence. Statistical models surface signals your analysts would take weeks to find manually.
Identify emerging fraud typologies before they reach your portfolio. Neural networks trained on cross-institutional patterns detect threats your historical rules cannot.
Every application sharpens the model. Continuous learning compounds your fraud defences over time — the opposite of static rule decay.
Cross-reference financials, behavioural patterns, and digital interactions to detect anomalies invisible to rules-based systems.
Cloud-native AI architecture with Australian-hosted and on-premise options for institutions with data sovereignty or APRA CPS 234 requirements.
Neural networks and ensemble methods trained on financial crime datasets. Continuously retrained to track evolving typologies — including synthetic identity and deepfake-generated applications.
Decisions in under a millisecond on high-volume application streams. Fast enough to intercept fraud at the point of application — not after settlement.
Cloud-native by default. On-premise or hybrid when required. Data stays within Australian jurisdiction — meeting APRA CPS 234, Privacy Act 1988, and SOC 2 requirements.
End-to-end encryption, role-based access controls, and full audit logging. Built to pass Australian prudential standards and enterprise security reviews.
HIDF integrates into your existing environment without ripping and replacing what you already have.
Integrate via API or secure data pipeline. HIDF ingests applicant records, transaction data, identity signals, and document metadata — alongside your existing systems.
Models evaluate financial behaviour, document integrity, digital footprints, and cross-referential patterns simultaneously. Every application and transaction gets a risk score with full explainability.
Risk scores, anomaly alerts, and diagnostic reports flow back into your decision engine in real time. Your team sees exactly why something was flagged — ready for audit, ready for action.
For institutions where fraud prevention is a regulatory obligation, not an afterthought. From APRA-regulated banks to fintechs preparing for AUSTRAC oversight.
Compounding fraud complexity across retail lending, commercial credit, and payments. HIDF delivers the diagnostic depth compliance and risk teams need — with the explainability AUSTRAC and APRA demand.
High application volumes, lean teams. HIDF automates deep applicant risk assessment — reducing manual review while catching the sophisticated fraud basic document checks miss.
You acquire customers entirely online — and so do fraudsters. Real-time behavioural analysis and identity risk scoring built for the speed of fully digital onboarding.
Fraud prevention that scales with growth — without ballooning headcount. API-first architecture integrates into your stack in days, not months.
75% of brokers were impacted by fraud in 2025. HIDF automates document verification and income validation — protecting your licence and your lender relationships.
Every major fraud vendor focuses on one piece of the puzzle. HIDF unifies all six signals at the point of application — the one moment where depth is decisive.
| Capability | Global Transaction Monitors NICE Actimize, Feedzai, etc. | Document Verification Tools Onfido/Entrust, Jumio, etc. | AML Screening Platforms ComplyAdvantage, etc. | HIDF Deep Application Intelligence |
|---|---|---|---|---|
| Pre-transaction application fraud detection | No | Partial | No | Yes |
| AI-generated document forensics | No | Partial | No | Yes |
| Multi-signal depth analysis (6 signals) | No | No | No | Yes |
| Explainable AI (regulator-ready) | Limited | No | Partial | Yes |
| Built for AUSTRAC / APRA / NCCP | No | No | No | Yes |
| Australian data sovereignty | No | No | No | Yes |
| Days to production (not months) | 6–12 mo | Weeks | Weeks | Days |
Category comparisons based on publicly available product documentation and analyst evaluations (Forrester APAC Wave Q4 2025). Individual vendor capabilities may vary.
Whether you own security, compliance, or architecture — HIDF was designed for the questions your board is asking.
Synthetic identity fraud is up 311%. AI-generated document fraud grew 5x in 2025. Your existing fraud stack was built for yesterday's threats. HIDF adds a depth layer that catches what transaction monitors miss — at the point of application, before losses occur.
Australian-hosted infrastructure. No offshore data processing. Full data sovereignty for APRA-regulated institutions.
The NCCP Act imposes responsible lending obligations with criminal and civil penalties. AUSTRAC Tranche 2 expands regulated entities from July 2026. HIDF was built for these specific obligations — not adapted from a US product with an Australian config file.
Every risk decision includes a complete, human-readable audit trail. When AUSTRAC asks why you flagged — or missed — an application, HIDF gives you the answer in seconds.
HIDF augments your existing fraud stack — no rip-and-replace. Documented REST APIs integrate with core banking, ERP, and onboarding systems. Cloud-native with on-premise options when APRA CPS 234 demands it.
We don't replace NICE Actimize or Feedzai. We catch what they were never designed to catch — at the application layer, before a dollar is at risk.
1 in 16 applications shows indicators of fraud. AI-generated document fraud grew 5x in 2025. Calculate your exposure.
These numbers are estimates. Your actual exposure could be higher. Get a personalised risk assessment based on your portfolio and application volumes.
Get a Personalised Risk Assessment — before July 2026Three scenarios showing exactly what legacy systems miss — and what HIDF's six-signal depth analysis catches.
Applicant purchases a deepfake payslip from an underground marketplace for $15. AI-generated bank statements show matching deposits. Claims $150K income for a $500K mortgage.
Documents look clean — AI-generated fakes are more consistent than real documents. Income matches bank statements. Standard document check: PASS.
Legitimate business - artificially created numbers, document presentation shows no imperfections, highly tuned statistics and data used to validate information provided. Multi-signal inconsistency → FRAUD DETECTED.
A real person inflates their income by 40% on a loan application, submitting edited bank statements that show higher balances and fabricated employer deposits.
Applicant is a real person with verified identity. Bank statements appear genuine at visual inspection. Credit score is acceptable. Application proceeds.
Statistical analysis flags deposit patterns inconsistent with claimed employer payroll cycles. Occupation income checked referencing statistical significance. Document edit timestamps don't match creation dates. Data consistency → INVESTIGATION REQUIRED.
Legitimate business with artificially created numbers or inflated numbers. Document presentation shows no imperfections. Generated using accounting programs and software.
Documents pass automated format validation. Numbers appear internally consistent. Standard OCR and template matching detect no anomalies. Software-generated documents are indistinguishable from legitimate originals.
HIDF catches it by using highly tuned statistics and data to validate information provided and various other digital footprint mechanisms. Financial figures cross-referenced against industry benchmarks and historical patterns reveal statistical improbabilities invisible to document-level checks. Multi-signal inconsistency → FRAUD DETECTED.
These aren't hypotheticals. AI-generated document fraud grew 5x in 2025. Synthetic identity fraud is up 311%. Your current systems weren't designed for this.
See HIDF in Action — Book a Briefing before July 2026Major regulatory reforms take effect from 1 July 2026 — the most significant expansion of Australian lending and financial crime regulation in a decade.
until AUSTRAC Tranche 2 & enhanced lending compliance obligations take effect
For the first time, AML/CTF obligations extend beyond financial institutions to:
Thousands of businesses must implement risk assessments, compliance programs, customer due diligence, and suspicious matter reporting — from zero.
The National Consumer Credit Protection Act 2009 imposes strict responsible lending obligations on all credit licensees:
Criminal and civil penalties for non-compliance, including potential loss of Australian credit licence. ASIC actively investigating lending fraud.
Four critical capabilities every regulated entity needs before July 2026. Check your readiness.
Can your system detect fabricated payslips, AI-generated bank statements, and inflated income claims against benchmarks at the point of application?
Can your AI explain its decisions in human-readable terms for AUSTRAC suspicious matter reports and APRA audit reviews?
Does your fraud platform meet APRA CPS 234 information security requirements, including Australian data residency and third-party provider oversight?
Are you meeting the NCCP Act's responsible lending obligations — reasonable inquiries, verification of financial situation, and suitability assessments — with documented procedures and technology in place?
Select the capabilities your institution currently has in place.
Built from day one for AUSTRAC, APRA CPS 234, the NCCP Act responsible lending obligations, and the Privacy Act 1988 — not retrofitted from a US product.
Deep analysis of the regulatory changes reshaping Australian financial crime prevention.
The most significant expansion of Australian AML/CTF regulation since the original 2006 Act. Who's affected, what's required, and the compliance gaps most institutions don't know they have.
Read more →1 in 3 borrowers misrepresent their financial position. AI-generated documents cost $15. A practical guide to meeting NCCP Act verification obligations when traditional checks can no longer detect fabricated applications.
Read more →Forrester's APAC Wave evaluated 9 fraud vendors — zero were Australian. Why data sovereignty, regulatory alignment, and local expertise matter more than global scale.
Read more →Synthetic identity fraud surged 311% in 12 months. AI-generated documents cost $15 on the dark web. Why single-signal detection is no longer enough — and what "depth" actually means.
Read more →AUSTRAC Tranche 2 expands AML/CTF obligations from July 2026. NCCP Act responsible lending enforcement is intensifying. AI-generated document fraud growing 5x year-on-year. The question isn't whether to act — it's whether you act in time.
30-minute confidential session. Tailored for CISOs, Compliance Officers, CROs, and CTOs. No commitment required.