28 October 2026
,
Lagos

FraudSense Nigeria 2026

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

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The New Frontlines of Fraud, Identity, and Trust
Nigeria is becoming one of the world’s most important test cases for AI-era fraud defence. Real-time payments now move at unprecedented scale through NIBSS Instant Payments, while AI-generated scams, synthetic identities, social engineering, insider compromise, and Fraud-as-a-Service are reshaping the country’s threat landscape. At the same time, Nigeria has become one of the first markets to introduce binding governance standards for AI and machine learning in financial crime detection.

As fraud becomes faster and more industrialised, institutions are rethinking how they detect, investigate, and respond. Real-time payment infrastructure, continuous identity assurance through BVN, NIN, and TIRMS, AI-enabled fraud operations, and cross-institutional collaboration are becoming central to protecting customers.

Hosted in Lagos, FraudSense Nigeria convenes senior leaders across banking, fintech, payments, and digital commerce tackling fraud, identity, and trust in the AI era. The summit examines AI compliance, real-time payment defence, identity beyond onboarding, and the fight against an industrialised fraud economy.

Why FraudSense, why now
0 B$
Annual electronic payment volume on Nigerian rails
0 M$
lost by banks to digital payment fraud in 2025
8 %
of all global synthetic documents originate from Nigeria
0
months to comply with CBN deadline for AI/ML governance
Who will be there
A cross-functional room of senior leaders tackling fraud, identity, and trust across Nigeria'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
Cross-functional by design
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

      From Progress to Pressure: Fraud Defence in the AI-Compliance Era

      Nigeria is having two firsts at once. Digital payment fraud losses fell 51 percent in 2025 — the first decline since 2021, credited to BVN-NIN integration, the CBN chargeback regime, and intensified NeFF coordination. In the same window, the CBN issued the world's first binding governance framework for AI and ML in financial crime detection — the March 2026 Baseline Standards introduce personal accountability for compliance officers and give Deposit Money Banks 18 months to comply. The institutional question is whether the operational gains hold as the AI-compliance discipline tightens, or whether 2025 was the floor, not the trend.
      • Fraud losses fell 51 percent in 2025. Which driver is most credit-worthy, and which is the most fragile if pressure resumes?
      • CBN's March 2026 AML/CFT standards now bind AI and ML in compliance with personal accountability for officers. What changes before the 18-month deadline?
      • AI augments the analyst today. What does the fraud operations function look like three years from now — and who runs it?
      • Agentic AI is in pilot now. What separates institutions building 18 months of operational learning from those still debating whether to start?

      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 Liability: Defending NIP at Quadrillion-Naira Scale

          NIBSS Instant Payments processed N1.07 quadrillion across 11.2 billion transactions in 2024 — a 79.6 percent value increase year on year, and the operational backbone of Nigeria's cashless economy. The CBN's chargeback regime now debits banks that receive fraud proceeds without due diligence. November 2025's APP fraud guidelines introduce joint reimbursement obligations and a 16-working-day investigation window. May 2026's BVN amendments add a 24-hour fraud watchlist and one-lifetime limits on linked phone number changes. The supervisory direction is clear: institutions carry more of the loss when fraud lands on their books. The operational question is whether real-time detection is moving fast enough to keep up with the supervisory expectation.
          • NIBSS processes 11 billion transactions a year on a rail designed for finality. Where does the institution add real-time friction without breaking commerce?
          • CBN's chargeback regime debits receiving banks for fraud proceeds. What separates the institutions catching mule transactions before settlement from those debited after?
          • APP fraud rules require joint investigation and shared liability within 16 working days. What does the institution build to investigate at that tempo?
          • 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

              Identity Is Not the Perimeter: BVN, NIN, TIRMS and Continuous Trust

              BVN was the foundation. NIN integration closed the impersonation and synthetic identity gaps. TIRMS — the Telecoms Identity Risk Management System — now connects banks to the mobile-number layer in real time to catch SIM-swap fraud before authentication clears. May 2026's BVN amendments restrict linked phone number changes to once in a lifetime and introduce a 24-hour fraud watchlist. Nigeria's identity stack is the strongest in Africa and one of the most ambitious in the world. But identity verification at onboarding is no longer the question — the question is what happens after. Social engineering bypasses the verified customer entirely. Insider compromise abuses access from inside the stack. AI-generated documents now defeat onboarding checks at industrial scale. The identity perimeter has to operate continuously, not at the gate.
              • BVN-NIN integration closed the impersonation gap at onboarding. What does the institution do when synthetic identity construction defeats document checks at industrial scale?
              • TIRMS gives real-time visibility into mobile-number activity. Where does that intelligence sit in the decisioning stack — pre-authentication, mid-session, or post-transaction?
              • Authentication is no longer a one-time event. Where does continuous trust assurance sit between BVN, NIN, device signal, and behavioural pattern?
              • Behavioural models profile how a human transacts. Where does identity assurance sit when the customer is an AI agent acting on their behalf?

              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

                The Scam Economy: Social Engineering, Insider Compromise, and AI at Industrial Scale

                Nigerian fraud has industrialised. The CBN and NeFF are explicit: social engineering, often aided by insider collusion, is now the dominant threat by both volume and value. The evidence is everywhere — AI-generated deepfakes of Nigerian public figures running live in investment scams; AI-crafted phishing achieving click-through rates four times the human-crafted average; Nigeria accounting for 8 percent of all synthetic documents observed in global identity-fraud reporting; voice-cloning, scam scripts, and victim data sold openly through Fraud-as-a-Service. The Yahoo Boy operating model has gone from individual hustle to commercialised supply chain. Defending the customer now means defending against persuasion the institution never sees.
                • Social engineering is now the dominant fraud threat by value. Where does the institution intervene when the customer believes the conversation is genuine?
                • Insider compromise is documented in over half of high-value incidents. What does the institution monitor for privileged-access employees that it doesn't today?
                • AI voice clones and public-figure deepfakes defeat customer instinct before the bank's model sees them. Where does the warning still land?
                • The Yahoo Boy operating model has industrialised through Fraud-as-a-Service. What separates the institution coordinating disruption from the one absorbing the loss?

                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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