28 July 2026
,
Johannesburg

FraudSense South Africa 2026

South Africa's dedicated event on fraud, identity, and trust in the AI era

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The New Frontlines of Fraud, Identity, and Trust
South Africa is facing one of the fastest-growing waves of digitally enabled fraud, with fraudsters increasingly bypassing systems by manipulating customers directly. SIM-swap attacks, deepfake impersonation, synthetic identities, and AI-generated social engineering are scaling across the country's financial and digital commerce ecosystem faster than traditional controls can adapt.

At the same time, the growth of PayShap and real-time payments is increasing the speed, complexity, and reach of fraud. Institutions are being forced to rethink how they detect, investigate, and respond to threats that operate at machine speed.

In response, FraudSense South Africa convenes senior leaders across banking, fintech, payments, and digital commerce who are tackling fraud, identity, and trust in the AI era. The summit examines how institutions are deploying AI-driven detection and investigation models, renegotiating liability as scams move at machine speed, and protecting the customer trust the country's digital economy depends on.

Why FraudSense, why now
0 %
increase in deepfake fraud incidents YoY
0 B+
ZAR of banking fraud losses in 2025, up 23% YoY
210 M+
in financial losses linked to banking fraud in 2025
0 B+
digital payments processed annually in South Africa
Who will be there
A cross-functional room of senior leaders tackling fraud, identity, and trust across South Africa's financial and digital commerce ecosystem.
ROLES

Chief Risk Officers
Chief Compliance Officers
Heads of Fraud & Financial Crime
Heads of Fraud Analytics
Heads of Payments Risk
Heads of Identity

ORGANISATION TYPES

Banks & Digital Banks
Fintechs
Payments Services Providers
E-commerce & Digital Commerce
Telecoms & Mobile Operators
Regulators & Infrastructure

What makes FraudSense unique
Built for institutions defending trust in the AI era
Built around live operational pressure
FraudSense is designed around the operational problems institutions are dealing with now — AI-generated scams, synthetic identities, APP fraud, mule networks, deepfake impersonation, and machine-speed social engineering. The agenda focuses on investigation realities, AI-driven response models, reimbursement pressure, detection workflows, and implementation challenges facing fraud and financial crime teams.
Cross-functional by design
Modern fraud no longer sits inside a single function or institution. FraudSense convenes senior leaders tackling fraud, identity, and trust in the AI era — reflecting how fraud now moves fluidly across organisational silos, customer channels, payment rails, digital platforms, marketplaces, and financial ecosystems. The room is structured to surface the conversations that cannot happen one function at a time.
A playbook for the AI era
The summit focuses on how institutions are using AI to strengthen fraud defence across the customer lifecycle — from identity and authentication through to detection, intervention, investigation, and recovery. Discussions are operational rather than theoretical, centred on what is already working, where institutions are struggling, and how defence models are evolving as both fraud and response increasingly operate at machine speed.
Agenda

8:00

9:00

Registration

    9:00

    9:05

    Opening Remarks

      9:05

      9:35

      AI vs AI: South Africa's Fraud Arms Race Has Already Started

      South African institutions are operating inside a machine-speed fraud economy where attackers and defenders both deploy AI-assisted capability. Criminal syndicates run deepfake impersonation, synthetic identity generation, adaptive scams, and automated social engineering at industrial scale, while institutions race to rebuild defence around behavioural intelligence, orchestration, and real-time decisioning. Trust itself is collapsing as a defensible signal — voice, video, and document evidence can be generated faster than institutions can verify them. The arms race is here and widening. That scale is no accident: fraud capability is now sold as a service — deepfake services, synthetic-identity kits, and scam frameworks that let low-skill actors attack at professional grade.
      • Fraud capability is now sold as a subscription service. What breaks first when professional-grade attacks come from low-skill actors at volume?
      • Attackers now deploy AI at industrial scale — synthetic identities, cloned voices, adaptive scams. Where does behavioural intelligence materially outperform rule-based detection?
      • Banks answer fraud questions with IT-security posture. Where does the institution separate fraud-ops accountability from IT, and own each properly?
      • The next fraud stack must counter AI threats the current one was never designed for. What does a three-year, AI-ready architecture have to look like?

      9:35

      9:50

      How We Solved...

      A practical case study on a real industry challenge, the approach taken, and results achieved.

        9:50

        9:55

        The Room Speaks: Morning Pulse

        A live audience pulse check capturing the priorities, pressures, and challenges shaping fraud and financial crime defence today.

          9:55

          10:25

          Real-Time Rails, Real-Time Models: Pre-Settlement Intercept as the New Defensive Standard

          PayShap has crossed 30 million transactions on rails that clear in seconds and are irreversible by design. The defensive answer emerging across the major banks is the same: score every transaction against the customer's behaviour in milliseconds, and hold suspect payments before they clear rather than chase them after. South African public disclosures in early 2026 documented beneficiary-analysis detection cutting EFT fraud by 80 percent within six months of deployment. The question is whether pre-settlement intercept becomes the sector standard fast enough.
          • 89% of fraud leaders call instant payments a high fraud risk. Does the rail's irreversible design outrun every control bolted onto it?
          • Pre-settlement hold is becoming the SA defensive pattern. What does real-time behavioural scoring require to hold a payment without breaking the rail?
          • Behavioural models flag transactions the customer authorised and passed facial ID on. Where is the line between intercepting fraud and overriding the customer?
          • Fraud and AML run as separate workflows on the same criminal enterprise. Where does convergence happen at rail speed, not in policy?

          10:25

          10:40

          How We Solved…

          A practical case study on a real industry challenge, the approach taken, and results achieved.

            10:40

            11:15

            Networking Break

              11:15

              11:45

              Device-Layer Trust Has Failed: Injection Attacks, Reverse-Splicing, and Accessibility Abuse on the Android Stack

              Deepfake-driven fraud in South Africa surged sharply year on year, and the dominant attacks no longer test the model — they bypass it. Injection attacks feed AI-generated streams straight into verification, defeating the camera entirely. Reverse-splicing overlays a stolen biometric onto the attacker's live face mid-check. Accessibility-service abuse operates inside legitimate banking apps, reading screens and automating clicks while the customer believes the session is genuine. The control passed. The person never existed. Or worse — the person never authorised.
              • Injection attacks and reverse-splicing bypass liveness through virtual devices and biometric overlay. Where does liveness detection have to sit to survive them?
              • Accessibility-service abuse runs inside legitimate apps at industrial scale. Where does behavioural detection sit without breaking the legitimate accessibility case for vulnerable customers?
              • A single synthetic face has been reused thousands of times across platforms. What does detection catch when the fraud is industrialised, not one-off?
              • FICA permits remote biometric verification assuming liveness works; POPIA treats biometrics as special data. What is the bank's exposure when synthetic identity passes?

              11:45

              12:00

              How We Solved...

              A practical case study on a real industry challenge, the approach taken, and results achieved.

                12:00

                12:30

                Duty of Care: When the Model Sees the Scam First

                Real-time detection now sees scam signals with high confidence before the customer presses send — and South African banks are being pushed into a role they never formally accepted: arbiter of whether a customer's instruction can be trusted. As scam losses mount and AI-generated manipulation replaces technical compromise, the question of who absorbs the loss is moving from legal theory to daily operational reality. The panel examines where the duty of care now begins when the model knew.
                • Banks increasingly hold strong scam signals before a payment completes. At what model confidence does inaction become a failure of duty of care?
                • Reimbursement-by-default shifts the loss onto institutions. Does it reduce AI-scaled scams at source, or just move the cost without changing fraudster economics?
                • Blocking a customer-authorised payment introduces paternalism and false-positive risk. Where is the defensible line between protecting a customer and overriding model error?
                • When a customer disputes the loss, authentication records are treated as proof of consent. Where does that evidence stop proving intent in an AI-scam era?

                12:30

                12:45

                How We Solved…

                A practical case study on a real industry challenge, the approach taken, and results achieved.

                  12:45

                  12:50

                  The Room Speaks: Closing Pulse

                  A final audience reflection measuring how perspectives shifted across the morning's discussions.

                    12:50

                    12:55

                    Closing Remarks

                      12:55

                      14:00

                      Networking Lunch

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