Melbourne Fraud and Financial Crime Technology Summit 2027

Beat the rush and join us early for complimentary barista-made coffee and breakfast.

With the Scams Prevention Framework now embedded across banks, telcos, and digital platforms, this opening keynote takes stock of what a year of shared accountability has actually delivered: where cross-sector collaboration has genuinely disrupted scams, and where the gaps regulators warned about are still showing up in practice.

• How organisations have moved from interpreting the framework's requirements to embedding them into daily fraud operations, and what that transition has actually looked like.
• An honest assessment of where collaboration between sectors has fallen short of the framework's intent, and what's driving the gap.
• Where reimbursement obligations, AFCA's expanded role, and evolving reasonable steps expectations are heading next.

After a near-miss involving a convincing deepfake voice call attempting to authorise a large funds transfer, one financial crime leader built a detection and verification framework specifically designed to catch AI-generated fraud attempts before they succeeded.

• How the team used a caught attempt as the catalyst for systemic change, rather than treating it as a one-off close call.
• Designing additional verification steps for high-risk transaction types without slowing down the vast majority of legitimate customer interactions.
• How human judgement and escalation protocols were rebuilt alongside the technical detection layer.

As institutions deploy increasingly sophisticated AI to detect fraud while criminals use the same class of technology to evade it, this panel examines the governance, explainability, and investment decisions shaping how organisations compete in an accelerating AI-versus-AI fraud battleground.

• How institutions are balancing increasingly complex detection models against the need to explain and justify decisions to regulators, customers, and disputes bodies.
• How quickly criminal use of AI is forcing detection models to be retrained and rearchitected, and whether defenders are keeping pace.
• Identifying the fraud scenarios where experienced human analysts continue to catch what AI systems miss, and why that gap persists.

Behind almost every successful scam sits a network of mule accounts moving stolen funds beyond reach. Hear how one team shifted focus from individual scam detection to the underlying mule account infrastructure that makes large-scale financial crime possible, and what disrupting that infrastructure requires.

• How focusing purely on the deceptive transaction misses the reusable infrastructure that criminals depend on across multiple scams.
• Emerging approaches to detecting mule account recruitment and onboarding patterns, rather than only catching suspicious activity after funds have already moved through them.
• Why effectively dismantling mule networks requires coordinated action across multiple banks and platforms simultaneously, and what's standing in the way of that coordination today.

A hands-on, interactive session working through a real fraud and financial crime scenario as a room. Details announced soon.

Detecting market abuse at scale is no longer just a compliance challenge; it's a data problem. Hear how one organisation embedded advanced AI into its surveillance platform to improve detection accuracy, reduce false positives, and scale consistently across complex global regulatory environments.

• Embedding AI into surveillance: how advanced analytics and machine learning are transforming detection accuracy while reducing noise and false positives.
• Scaling across borders: navigating diverse regulatory requirements while deploying a consistent, enterprise-wide surveillance capability.
• From insight to action: operationalising AI-driven alerts to enable faster investigations, stronger compliance outcomes, and real business impact.

Facing customer complaints about excessive verification steps while simultaneously under regulatory pressure to strengthen fraud controls, one fraud leader redesigned the customer authentication journey to apply friction only where risk genuinely warranted it.

• How the team identified specific points in the journey where security steps were driving abandonment without meaningfully reducing fraud.
• Designing a system that dynamically adjusted verification requirements based on transaction risk signals, rather than applying uniform friction to every interaction.
• How the team demonstrated to both the business and the regulator that fraud losses decreased even as customer friction and complaints fell.

As financial crime increasingly spans institutions, sectors, and technology platforms, this panel tackles the unresolved question of where responsibility should sit when scams succeed, and what that means for organisational culture, incentives, and long-term customer trust.

• Why frameworks built around individual organisational responsibility struggle to address crime that deliberately exploits the seams between institutions.
• How organisations are building internal cultures where employees ask uncomfortable questions and challenge control gaps, rather than relying solely on technical safeguards.
• What further regulatory change industry leaders anticipate around shared liability, and how organisations are positioning themselves ahead of it rather than reacting after the fact.

Small-group, discussion-based sessions where you'll work through real fraud and financial crime challenges with peers in similar roles. Roundtable topics will be announced soon.

Put your knowledge to the test in this fast-paced quiz covering real-world trivia, key concepts, and emerging trends. Compete for bragging rights — and a voucher — as the top scorer takes the crown.

After early attempts at intelligence sharing stalled under legal and privacy objections, one financial crime leader built a framework for cross-institution collaboration that satisfied compliance and privacy teams while still delivering genuinely actionable shared intelligence.

• What specific privacy and data-sovereignty concerns derailed earlier information-sharing efforts, and why simply pushing harder wasn't the answer.
• How the team identified which categories of intelligence could be shared safely and usefully, rather than attempting to share everything and negotiating exceptions.
• How the framework ensured shared data actually changed detection and response behaviour across participating institutions, rather than sitting unused in a shared repository.

With scam losses continuing despite improved detection and disruption capability, this closing keynote turns to an underexplored dimension of financial crime response: how institutions rebuild trust and support customers through the aftermath of a scam, not just the moment of prevention.

• Why customers who fall victim to scams often feel abandoned by the same institutions that promised protection, and what that does to long-term trust and retention.
• How institutions are approaching reimbursement conversations under the Scams Prevention Framework in ways that either rebuild or further erode customer confidence.
• What leading organisations are learning from directly involving scam victims in improving detection and education efforts, rather than treating each case purely as a closed file.

With synthetic identities, deepfakes, and AI-generated documentation increasingly bypassing traditional verification processes, this session brings together identity, KYC, and technology leaders to discuss what robust customer verification actually requires now.

• How AI-generated identity documents and deepfake verification attempts are exposing the limits of processes built for a pre-AI threat environment.
• How institutions are strengthening identity checks without making legitimate customer onboarding prohibitively slow or frustrating.
• What role cross-institution and industry-utility approaches to identity verification could play in closing gaps no single organisation can close alone.

Unwind with your peers for a couple of drinks on us!

Beat the rush and join us early for complimentary barista-made coffee and breakfast.

With the Scams Prevention Framework now embedded across banks, telcos, and digital platforms, this opening keynote takes stock of what a year of shared accountability has actually delivered: where cross-sector collaboration has genuinely disrupted scams, and where the gaps regulators warned about are still showing up in practice.

• How organisations have moved from interpreting the framework's requirements to embedding them into daily fraud operations, and what that transition has actually looked like.
• An honest assessment of where collaboration between sectors has fallen short of the framework's intent, and what's driving the gap.
• Where reimbursement obligations, AFCA's expanded role, and evolving reasonable steps expectations are heading next.

After a near-miss involving a convincing deepfake voice call attempting to authorise a large funds transfer, one financial crime leader built a detection and verification framework specifically designed to catch AI-generated fraud attempts before they succeeded.

• How the team used a caught attempt as the catalyst for systemic change, rather than treating it as a one-off close call.
• Designing additional verification steps for high-risk transaction types without slowing down the vast majority of legitimate customer interactions.
• How human judgement and escalation protocols were rebuilt alongside the technical detection layer.

As institutions deploy increasingly sophisticated AI to detect fraud while criminals use the same class of technology to evade it, this panel examines the governance, explainability, and investment decisions shaping how organisations compete in an accelerating AI-versus-AI fraud battleground.

• How institutions are balancing increasingly complex detection models against the need to explain and justify decisions to regulators, customers, and disputes bodies.
• How quickly criminal use of AI is forcing detection models to be retrained and rearchitected, and whether defenders are keeping pace.
• Identifying the fraud scenarios where experienced human analysts continue to catch what AI systems miss, and why that gap persists.

Behind almost every successful scam sits a network of mule accounts moving stolen funds beyond reach. Hear how one team shifted focus from individual scam detection to the underlying mule account infrastructure that makes large-scale financial crime possible, and what disrupting that infrastructure requires.

• How focusing purely on the deceptive transaction misses the reusable infrastructure that criminals depend on across multiple scams.
• Emerging approaches to detecting mule account recruitment and onboarding patterns, rather than only catching suspicious activity after funds have already moved through them.
• Why effectively dismantling mule networks requires coordinated action across multiple banks and platforms simultaneously, and what's standing in the way of that coordination today.

A hands-on, interactive session working through a real fraud and financial crime scenario as a room. Details announced soon.

Detecting market abuse at scale is no longer just a compliance challenge; it's a data problem. Hear how one organisation embedded advanced AI into its surveillance platform to improve detection accuracy, reduce false positives, and scale consistently across complex global regulatory environments.

• Embedding AI into surveillance: how advanced analytics and machine learning are transforming detection accuracy while reducing noise and false positives.
• Scaling across borders: navigating diverse regulatory requirements while deploying a consistent, enterprise-wide surveillance capability.
• From insight to action: operationalising AI-driven alerts to enable faster investigations, stronger compliance outcomes, and real business impact.

Facing customer complaints about excessive verification steps while simultaneously under regulatory pressure to strengthen fraud controls, one fraud leader redesigned the customer authentication journey to apply friction only where risk genuinely warranted it.

• How the team identified specific points in the journey where security steps were driving abandonment without meaningfully reducing fraud.
• Designing a system that dynamically adjusted verification requirements based on transaction risk signals, rather than applying uniform friction to every interaction.
• How the team demonstrated to both the business and the regulator that fraud losses decreased even as customer friction and complaints fell.

As financial crime increasingly spans institutions, sectors, and technology platforms, this panel tackles the unresolved question of where responsibility should sit when scams succeed, and what that means for organisational culture, incentives, and long-term customer trust.

• Why frameworks built around individual organisational responsibility struggle to address crime that deliberately exploits the seams between institutions.
• How organisations are building internal cultures where employees ask uncomfortable questions and challenge control gaps, rather than relying solely on technical safeguards.
• What further regulatory change industry leaders anticipate around shared liability, and how organisations are positioning themselves ahead of it rather than reacting after the fact.

Small-group, discussion-based sessions where you'll work through real fraud and financial crime challenges with peers in similar roles. Roundtable topics will be announced soon.

Put your knowledge to the test in this fast-paced quiz covering real-world trivia, key concepts, and emerging trends. Compete for bragging rights — and a voucher — as the top scorer takes the crown.

After early attempts at intelligence sharing stalled under legal and privacy objections, one financial crime leader built a framework for cross-institution collaboration that satisfied compliance and privacy teams while still delivering genuinely actionable shared intelligence.

• What specific privacy and data-sovereignty concerns derailed earlier information-sharing efforts, and why simply pushing harder wasn't the answer.
• How the team identified which categories of intelligence could be shared safely and usefully, rather than attempting to share everything and negotiating exceptions.
• How the framework ensured shared data actually changed detection and response behaviour across participating institutions, rather than sitting unused in a shared repository.

With scam losses continuing despite improved detection and disruption capability, this closing keynote turns to an underexplored dimension of financial crime response: how institutions rebuild trust and support customers through the aftermath of a scam, not just the moment of prevention.

• Why customers who fall victim to scams often feel abandoned by the same institutions that promised protection, and what that does to long-term trust and retention.
• How institutions are approaching reimbursement conversations under the Scams Prevention Framework in ways that either rebuild or further erode customer confidence.
• What leading organisations are learning from directly involving scam victims in improving detection and education efforts, rather than treating each case purely as a closed file.

With synthetic identities, deepfakes, and AI-generated documentation increasingly bypassing traditional verification processes, this session brings together identity, KYC, and technology leaders to discuss what robust customer verification actually requires now.

• How AI-generated identity documents and deepfake verification attempts are exposing the limits of processes built for a pre-AI threat environment.
• How institutions are strengthening identity checks without making legitimate customer onboarding prohibitively slow or frustrating.
• What role cross-institution and industry-utility approaches to identity verification could play in closing gaps no single organisation can close alone.

Unwind with your peers for a couple of drinks on us!