Rewiring the Banker for the Age of Intelligence

We are living through the fastest technology transition in the history of finance. Reasoning models now outperform expert humans on medical and legal licensing exams. Multimodal AI reads documents, interprets charts and listens to calls in real time. Agentic AI systems execute multi-step tasks autonomously — booking, transacting, reconciling — without a human in the loop. And the cost of intelligence has fallen by more than 99% in three years.

For banks, this is not a background trend. It is a structural disruption arriving simultaneously on every front: customer experience, credit decisioning, fraud detection, compliance, treasury, wealth management and the operating model itself. The question is no longer whether AI will transform your institution — it is whether your leadership team will shape that transformation or be shaped by it.

This two-day Bootcamp is built around three convictions: that understanding must be current (the AI landscape of six months ago is already obsolete); that strategy must be hands-on (knowing about AI is not the same as knowing how to use it); and that decisions must be made. By the end of Day Two, every participant will have built a draft AI Bank concept — stress-tested by peers and ready to take to their board.

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Skills to be gained

Shape executive strategies for future banking

Lead technology-driven transformation

Strengthen decision-making and governance

Design customer-first product innovations

Manage data, ethics and trust

Drive organisational change

Expand peer networks across the region

Areas to be covered

Banking in an intelligent economy

Evolving technology architecture

Data governance and cybersecurity

Customer engagement and new products

Leadership and talent strategies

Fairness, ethics and trust

Regulatory models and public policy

Strategic Briefing · Banking AI Bootcamp 2026

The Landscape Has Changed: What Bankers Must Know Now

The five developments below define the strategic context for this Bootcamp. They are not predictions — they are live deployments reshaping competitive advantage in banking right now.

01
Foundational banking models

The new competitive moat

Banks are moving from fragmented AI use cases to unified models trained on proprietary data. Competitive advantage is no longer the algorithm. It is the depth and structure of your data.

Banks are moving from fragmented AI use cases to unified models trained on proprietary data. Competitive advantage is no longer the algorithm. It is the depth and structure of your data.

Read More
02
Agentic core banking architecture

Moving beyond applications

AI agents are beginning to orchestrate banking processes across systems. Over time, business logic shifts out of applications and into an agent layer, changing how banks are built.

AI agents are beginning to orchestrate banking processes across systems. Over time, business logic shifts out of applications and into an agent layer, changing how banks are built.

Read More
03
The end of the interface

AI becomes the front end

AI is replacing traditional interfaces across enterprise systems. For banks, this changes how customers interact, how workflows operate, and how vendors integrate.

AI is replacing traditional interfaces across enterprise systems. For banks, this changes how customers interact, how workflows operate, and how vendors integrate.

Read More
04
Agent-to-agent commerce

A near-term reality

Transactions will increasingly be negotiated and executed by AI agents. Customer journeys, pricing models and authentication frameworks will need to be redesigned.

Transactions will increasingly be negotiated and executed by AI agents. Customer journeys, pricing models and authentication frameworks will need to be redesigned.

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05
The regulatory reckoning

From principles to enforcement

AI governance is now being enforced through regulation. Boards must address model risk, explainability and accountability across all AI-driven functions.

AI governance is now being enforced through regulation. Boards must address model risk, explainability and accountability across all AI-driven functions.

Read More
Foundational Banking Models: The New Competitive Moat

The most consequential development in banking AI is not a chatbot or a copilot — it is the emergence of domain-specific foundational models trained on proprietary banking event sequences. Revolut's PRAGMA (April 2026) is the most advanced public example: a single pre-trained backbone that simultaneously outperforms task-specific models across credit scoring, fraud detection, lifetime value prediction, product recommendation and more. Stripe, Mastercard and Visa have all announced comparable models. The moat is no longer the algorithm — it is proprietary data at scale. Any bank sitting on comparable transaction volumes could build its own version. Most are not.

Read More
The Agentic Core Banking Architecture: Moving Beyond Applications

Today's bank technology estate is built around vertical application silos — lending, treasury, payments, CRM — each a walled garden connected by brittle integration layers. A rigorous new practitioner framework describes the three-phase migration path out of this architecture: Phase 1, agents orchestrate across existing systems via API; Phase 2, new products are built as pure agentic processes and business logic begins migrating out of applications; Phase 3, applications flatten to data access layers and the concept of a 'banking application' becomes obsolete. The critical implication: data governance investment must precede architectural migration, not follow it.

Read More
MCP and the Death of the Interface

Anthropic's Model Context Protocol — now backed by OpenAI, Google, Microsoft and AWS under the Linux Foundation — has fundamentally changed how enterprise software is built. Major platforms including Slack, Figma and Asana now embed their interfaces directly inside AI chat windows. The app becomes a backend; the interface is owned by the AI. For banks, every customer touchpoint, every workflow tool and every vendor relationship must be re-evaluated against an agentic architecture.

Read More
Agent-to-Agent Commerce: The 12-Month Horizon

When a customer's AI agent negotiates with a bank's AI agent to arrange a mortgage, the entire customer journey, pricing logic, authentication framework and relationship model must be redesigned. Early agent-to-agent payment rails are already live on Stripe's Agent Commerce Protocol. Banks that have not begun designing for this world are already behind — and foundational models make the gap wider still.

Read More
The Regulatory Reckoning

The EU AI Act is now in force for high-risk applications including credit scoring, KYC and fraud systems. Bank Negara Malaysia and MAS Singapore have both issued updated guidance on model risk, algorithmic fairness and AI governance. Boards must understand what this means for model documentation, explainability requirements and third-party vendor oversight — especially when a single foundational model underlies multiple regulated functions simultaneously.

Read More
Pre-Bootcamp Preparation
  • Pre-reading pack distributed three weeks before the event — including practitioner perspectives on foundational banking models, agentic core banking architecture, current BNM and MAS guidance, and selected chapters from Building the AI Bank by Emmanuel Daniel
  • Pre-event survey: a 15-minute diagnostic to calibrate session depth and identify the specific architecture challenges and competitive pressures most relevant to the group
  • Tech setup guide: instructions for accessing Claude and the lab session tools, with a 30-minute self-paced orientation for participants new to frontier AI tools
  • Optional pre-bootcamp webinar: a 60-minute orientation session one week before the event
Post-Bootcamp Deliverables
  • Proceedings Report summarising key insights, areas of consensus and the AI Bank concepts from the Capstone — shared within 48 hours
  • All presentation materials and lab guides, including agent design frameworks, foundational model assessment templates and Capstone project materials
  • Each participant's AI Bank concept document and agent design documentation, formatted for internal handover
  • Delegate contact directory and LinkedIn group for ongoing peer exchange
  • One-year membership to The Banking Academy's Future Bank Working Group — quarterly briefings, webinars and research
  • Optional: 60-minute follow-up strategy session with a Banking Academy associate within 60 days

Who should attend

Chairmen and board members of traditional and digital banks

CEOs and senior management

Heads of strategic planning, innovation and business development

Heads of AI, data, analytics, cybersecurity, channels and distribution

Senior managers driving AI adoption across banking functions

Regulators and policymakers shaping AI governance in financial services

AI Banking Bootcamp · Programme Format

Types of Sessions

Expert Briefing

A structured intelligence briefing on live deployments and current developments, followed by facilitated discussion.

Hands-On Lab

Participants work directly with AI tools on real banking scenarios. Laptops required. Output produced during the session.

Architecture Workshop

Small groups interrogate a live architectural question — applying the three-phase core banking migration model or the PRAGMA paradigm to their own institution.

Structured Dialogue

SmallFacilitated peer discussion using real-world scenarios and challenge cards.

Build Sprint

Participants use AI to construct a real deliverable in real time — a workflow, agent design, policy draft or strategy document.

Capstone Project

Groups design a functioning AI Bank concept, using AI to produce their presentation deck or prototype live — presented to peers at the close of Day Two.

The Programme

Building the AI Bank Bootcamp Africa 2026 | Cape Town, South Africa

6 October 2026

18:00 – 20:00

Welcome Networking Cocktail — Meet fellow participants, faculty and guest speakers. Introduction to bootcamp themes and preparation guide for Day One.


7 October 2026

07:30 – 08:30

Arrival, Breakfast & Registration | Device setup for lab sessions

08:30 – 09:30

Opening Session: The State of AI in Banking — What Has Actually Changed in the Last 18 Months

Expert Briefing

A rapid-fire intelligence briefing grounded in what is actually deployed, not what is promised. We move fast, stay concrete, and challenge assumptions from the first minute.

  • Reasoning models: what frontier AI can now do for credit, compliance and risk that previous AI could not
  • The agentic turn: from chatbot to autonomous operator — live deployments at leading global institutions
  • Foundational banking models: PRAGMA, Stripe, Mastercard and Visa — the convergence that marks a new competitive layer in financial AI
  • MCP and the death of the interface: why agentic architecture changes every vendor relationship and customer touchpoint
  • Cost collapse: competitive advantage now depends on data quality and organisational capability, not model access
  • The 12-month horizon: agent-to-agent commerce, AI-native competitors — the decisions you need to make now

09:45 – 11:00

Lab Session: Stress-Testing Your Institution in an Agentic World

Hands-On Lab | Laptops required

We skip basic prompting and go straight to the strategic question that matters most: what happens to your bank when your customers have AI agents, your competitors have foundational models, and your core banking architecture is still organised around application silos?

  • Part 1 — Competitive stress-test: map your institution’s most vulnerable revenue lines and customer relationships against a competitor running a PRAGMA-style foundational model. Output: a ranked agentic exposure map for your bank
  • Part 2 — Agent build: design and deploy a functional AI agent for a real banking task — credit pre-screening, regulatory monitoring, customer query triage or treasury alerting. Define objectives, connect to a simulated data source, run and debug the agent, add policy constraint layer
  • Take-away: a documented agent design and competitive risk map, ready to share with your technology and strategy teams

11:00 – 11:20

Coffee & Discussion Break

11:20 – 12:30

Session 2: Agentic AI in Banking — The Hard Problems Boards Are Not Asking Yet

Tutorial

This session examines the live governance, liability and architecture questions practitioners are wrestling with now — not introductory framing.

  • Authentication and identity in an agentic world: verifying AI agent claims, liability frameworks for agent errors
  • Orchestration architectures: single-agent vs. multi-agent systems — why the manager-agent pattern is becoming the dominant enterprise model
  • Agent memory and context: persistent memory, retrieval-augmented generation and the privacy implications for banking
  • The MCP ecosystem in banking: which institutions are building MCP-compatible infrastructure today and what the 'headless bank' looks like
  • Guardrails and governance: the operational mechanisms that actually work at scale
  • Discussion: identify the three banking processes most exposed to agent disruption — and three where you could deploy agents for competitive gain

12:30 – 14:00

Lunch | Facilitated Peer Tables

14:00 – 15:15

Session 3: Foundational Models in Banking — PRAGMA, the New Competitive Moat and Your Data Strategy

Tutorial

This session examines the most consequential architectural development in financial AI — institution-wide foundational models trained on proprietary banking event sequences — and works through the strategic and data governance implications.

  • What PRAGMA actually is: Revolut's encoder-style Transformer trained on 40 billion banking events, scaling from 10M to 1B parameters — one backbone replacing all siloed task-specific models
  • The architecture in plain terms: key-value-time tokenisation, two-encoder branch design, LoRA fine-tuning on 1–2% of parameters outperforming full retraining
  • Competitive implications: Stripe, Mastercard and Visa have all announced comparable models. The moat is now data, not algorithm
  • What this means downstream: when credit scoring, fraud, LTV and product recommendation all run from the same foundational model, updating the backbone improves every function simultaneously
  • Workshop: assess your institution's data estate against foundational model requirements — what do you have, what is missing, and what is the 18-month path to close the gap?

15:15 – 15:35

Afternoon Break

15:35 – 16:40

Session 4: What Does a Fully AI-Native Core Banking System Look Like? Dismantling the Application Silo Model

Design Workshop

Most AI-in-banking discussions focus on use cases. This session addresses the harder question: what does a bank's entire technology architecture look like when rebuilt for an agentic, foundational-model world?

  • The diagnosis: vertical application silos — lending, treasury, payments, CRM — each a walled garden, kept in sync through ETL pipelines that generate a disproportionate share of production incidents
  • Phase 1 (Agentic Orchestration): agents call existing applications via API — immediate value, no systems change required
  • Phase 2 (Logic Migration): new products built as agentic processes; business logic migrates out of application layers; hardcoded rules become visible as constraints
  • Phase 3 (Application Thinning): applications flatten to data access layers; the concept of a 'banking application' becomes obsolete
  • Architecture workshop: apply the three-phase model to your institution — where are you today, what is the primary constraint, what would Phase 3 look like for your regulatory environment?

16:40 – 17:30

Session 5: Organising for AI — Talent, Teams and the Structures That Work

Structured Dialogue

AI transformation fails most often not because of technology but because of organisational design. This session draws on case studies from institutions that have succeeded and those that have stalled.

  • Where should AI teams sit? Centralised lab vs. embedded squads vs. the hybrid centre-of-excellence model emerging as dominant in regulated institutions
  • New roles in practice: what a Chief AI Officer, AI Product Manager and AI Risk Officer actually do
  • Reskilling at scale: the workforce transformation programmes working in banking, including the DBS AI literacy programme
  • The 'last mile' problem: why AI pilots succeed and enterprise rollouts fail — the cultural, incentive and governance factors that kill promising programmes
  • Structured dialogue: map your institution's AI capability maturity and identify the single most important organisational intervention needed

17:30

End of Day One


8 October 2026

07:30 – 08:30

Breakfast

08:30 – 09:45

Session 6: Leading Global Bank AI Deployments — What Is Actually Being Built

Case Studies

A deep dive into the specific AI programmes underway at leading global institutions — not press releases, but operational realities, architectural choices, lessons learned and competitive implications.

  • Global tier-1 deployments: LLM-powered research suites deployed to tens of thousands of employees; AI code generation at scale; trade finance document processing using multimodal AI; next-best-action systems generating documented revenue uplift
  • The foundational model arms race: how PRAGMA-class architectures compare to what the major card networks have built — and what this means for deposit-taking institutions lacking comparable event-scale data
  • European and regional deployments: AI risk and compliance monitoring, AI credit underwriting, conversational banking pilots, autonomous savings triggers — what scaled and what stalled, and why
  • Discussion: which deployment model is most directly applicable to your institution, and what would it take to replicate or leapfrog it within 18 months?

09:45 – 10:00

Break

10:00 – 11:00

Session 7: Ethics, Bias and Algorithmic Trust — It Is in the Plumbing

Structured Dialogue

Ethics is not a governance layer you add after the system is built — it is in the architecture, the data and the objective function from day one.

  • How bias enters AI systems in banking: data selection, labelling, objective function design and feedback loops — and the specific failure modes when a foundational model encodes historical discriminatory patterns
  • Speed without due process as the new ethical failure mode: cases where AI-accelerated decisions outran accountability structures
  • EU AI Act compliance in practice: what it looks like operationally when a single foundational backbone underlies multiple regulated functions simultaneously
  • BNM and MAS guidance: model documentation, explainability and the PURE framework (Purposeful, Unsurprising, Respectful, Explainable)
  • When AI manipulates: the ethics of autonomous personalisation and the boundary between helpful and manipulative AI in customer-facing banking

11:00 – 11:20

Coffee Break

11:20 – 12:20

Session 8: Cybersecurity in the AI Age — New Threats, New Defences

Tutorial

AI has fundamentally changed the threat landscape. The attack surface is now cognitive as well as technical — and agentic architectures create new vectors that conventional security frameworks were not designed to address.

  • New threat vectors: AI-generated fraud at scale, voice cloning, synthetic identity creation, and adversarial attacks on AI models — with documented cases from banking operations
  • When identity collapses: zero-trust architecture in an agentic world where the entity making a request may be an AI agent, a deepfake, or a legitimate customer
  • Foundational model security: prompt injection, adversarial perturbation of training data, and the tail risk of a single model failure cascading across credit, fraud, and compliance
  • Protocol risk: MCP and agent frameworks create new attack surfaces — including prompt injection, tool poisoning, and context manipulation
  • Post-quantum cryptography: NIST standards are now published; banks that have not begun migration planning face material operational risk by 2027–2028
  • Regulatory engagement: co-developing AI security frameworks with national regulators that align with the architecture being actively built

12:20 – 13:45

Lunch | Working lunch for Capstone Project preparation

13:45 – 15:30

Capstone Lab: Build Your AI Bank

Capstone Project | Laptops required

Working in groups of 3–4, participants design a concept for an AI Bank — built from scratch on agentic infrastructure, or a transformation roadmap for their existing institution. The constraint: you must use AI to build your own presentation.

  • Your AI Bank concept must address: the foundational model strategy; the core banking architecture migration path; the agentic product layer; the governance and ethics framework; and the 18-month build roadmap
  • Use Claude or equivalent AI to generate your deck, prototype or strategy document in real time during the session — not prepared in advance
  • Groups may produce a slide deck, working prototype, policy document or board narrative — all AI-built during the session
  • Every concept is stress-tested against three realities: what can you actually build? Who does this beat and how? Can a regulated institution actually operate this?

15:30 – 15:45

Afternoon Break | Final preparation for presentations

15:45 – 17:00

Closing Session: AI Bank Showcase — Present, Challenge, Commit

Hands-On Lab

The final session is where learning becomes accountability. Each group presents their AI Bank concept using the AI-built deck or application created in the Capstone Lab. No pre-prepared slides.

  • Each group presents for 8 minutes: foundational model strategy, core banking architecture path, first product, governance framework and 18-month milestone
  • Two rounds of structured peer challenge: 'What in this architecture would collapse under regulatory scrutiny?' and 'What competitive assumption have you not tested?'
  • Facilitator synthesis: the patterns across all group strategies, the common blind spots, and the data governance decisions that will differentiate leaders from followers
  • Each participant commits publicly to one specific AI initiative they will initiate within 30 days
  • Certificate presentation and programme close

17:00

End of Programme | Certificate Presentation & Group Photograph

Anchored by a highly qualified team of experts

The programme is anchored and delivered by some of the most experienced professionals in the industry.

Barry Katz
Emmanuel Daniel
Founder, TAB Global
Barry Katz
Juergen Rahmel
Global AI and Digital Innovation Expert Lecturer, University of Hong Kong
Axel-Winter
Axel Winter
Former Global Head
Enterprise Architecture & Tech Strategy
Standard Chartered
Tavonga-Muchuchuti
Tavonga Muchuchuti
Board Member, Africa Fintech Network
Global AI Policy Leader

The Investment

With Accommodation

US$ 5,800

  • Full access to Building the AI Bank Bootcamp Africa 2026
    (7 - 8 October 2026, Cape Town, South Africa).
  • Programme slides, reading materials and videos.
  • 3-night accommodation in Cape Town, South Africa
    (6 - 8 October 2026).
  • All program-related breakfasts and lunches.
  • Certificate of Participation
  • One year membership to Future Bank Working Group

*Excludes airfare, visa fees, airport transfers and dinners

Without Accommodation

US$ 5,000

  • Full access to Building the AI Bank Bootcamp Africa 2026
    (7 - 8 October 2026, Cape Town, South Africa).
  • Programme slides, reading materials and videos.
  • All program-related breakfasts and lunches.
  • Certificate of Participation
  • One year membership to Future Bank Working Group

*Excludes airfare, visa fees, airport transfers and dinners

Have a Query? Get in Touch with Us Today!

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