The Threat Landscape
How AI is turned against financial institutions
The evidence module. It walks you through how generative and agentic AI have rewritten the economics of financial crime: deepfake voice and video fraud, AI-synthesised identity documents, fraud-as-a-service, and multi-step, agent-driven schemes — anchored in the numbers and the named cases, including the South African picture. You leave able to describe the principal attack types, cite the leading evidence to make the internal case for AI-risk competency, and map your own institution's exposure surface.
- Describe the principal AI-enabled attack types now facing financial institutions and the direction of the trend lines.
- Cite the leading evidence, including the South African fraud data, to make the internal case for AI-risk competency.
- Recognise the institution's own exposure surface across onboarding, payments, advice and lending.
- Threat-model literacy
- Reading fraud and identity-verification reports critically
- Translating threat intelligence into desk-level vigilance
- Making the evidence-based internal case
Lessons in this module
How it lands across the four desks
Your desk sits at the sharp end of every attack type in this module: synthetic documents at onboarding, deepfake-authorised payments, and AI-automated schemes designed to move faster than a rules engine. You leave with the full attack taxonomy and the trend data behind it.
You own the exposure map. This module gives you the evidence base — regulator alerts, threat-intelligence data, the named cases — to brief a board, justify control spend, and document that the institution understood its threat environment.
Your clients and your own likeness are the raw material: deepfake investment scams using synthetic video of trusted figures, impersonation of advisers, and social-engineering built from scraped client data. You learn the patterns your clients will be hit with.
Manipulated and fabricated application inputs are your front line: AI-polished payslips, synthetic income narratives, and identities assembled specifically to pass onboarding and default later. This module shows you the industrialised supply chain behind them.
Key literature · 6 sources
Every module rests on a verified scholarly and institutional evidence base. The full core and further reading lists open with the module.
- Europol (2024) 'Internet Organised Crime Threat Assessment (IOCTA) 2024' — the fraud-as-a-service supply chain, including AI-generated identity documents sold to defeat onboarding.
- FinCEN (2024) 'Alert FIN-2024-Alert004: Fraud Schemes Involving Deepfake Media Targeting Financial Institutions' — the operational alert and red-flag indicators.
- FATF (2025) 'Horizon Scan: AI and Deepfakes — Impacts on ML/TF/PF' — the detection-lags-generation finding that frames the defensive posture.
- SABRIC (2024) 'Annual Crime Statistics 2023' — the South African loss and trend anchor, with generative AI named among drivers.
- SARB Prudential Authority & FSCA (2025) 'Artificial Intelligence in the South African Financial Sector' — adoption, risk rankings, the skills-shortage finding, and the announced discussion paper.
- U.S. Federal Reserve (2019) 'Synthetic Identity Fraud' payments-fraud insights — the definitional treatment of synthetic identities and bust-out patterns.