CFTE Capability Programme
A specialised programme that equips financial institutions serving micro, small and medium-sized enterprises with the knowledge and capabilities to apply AI and better support their SME clients.
It moves senior teams from broad interest in AI to practical institutional choices: where value lies for MSME clients, what to prioritise first, how to govern it responsibly, and what to do next.
Overview
AI is reshaping how financial institutions think about growth, risk, customer engagement and operating efficiency. For institutions serving MSMEs the opportunity is significant, and so is the difficulty of turning AI from broad interest into practical action that is realistic, affordable and responsibly governed.
This programme builds the strategic understanding, practical judgement and applied outputs that senior teams need to act. Through executive learning, practitioner insight, applied institutional work and focused support, participants clarify where AI can create value for their MSME clients, prioritise realistic use cases, and move closer to implementation in a way that fits their own context.
Every exercise is anchored to a live MSME challenge inside the participating institution.
Realistic interventions an institution can test within its existing constraints.
Outputs are judged on quality, pilot readiness and the contribution to MSME reach over time.
Learning outcomes
Build a shared executive view of how AI is changing financial services and MSME banking.
Identify where value may lie for MSME clients and what is realistically worth pursuing first.
Translate an idea into use case logic, data requirements and an implementation pathway.
Set the governance, accountability and control expectations that responsible AI requires.
Package the work so the institution can test, govern, fund or partner on the next step.
Who should attend
Designed for senior decision-makers in any institution serving micro, small and medium-sized enterprises.
Programme structure
A three-month executive journey that combines intensive in-person work at the start and the end with a guided application phase in between. Each institution works on one clearly defined challenge of its own.
Institutional diagnostic, challenge definition, participant onboarding and success criteria.
The AI reality for financial services leaders, use case identification and roadmap framing.
Coaching, clinics, structured working sessions and peer challenge, building the institutional output.
Expert review, practitioner critique, roadmap refinement and final presentation.
What has actually changed in the AI era, and what it means for MSMEs.
Live demonstrations of what current systems can and cannot do.
Where the technology is heading, and which decisions can wait.
Choosing between opportunities on value, feasibility and affordability.
Accountability, oversight and the controls a board will expect.
What has to change internally for any of it to hold.
How you will learn
Expert masterclasses led by practitioners sit alongside structured working sessions, thematic clinics, coaching, peer challenge across the cohort and expert review panels. Each institution works on one clearly defined challenge of its own and submits outputs at agreed milestones.
A curated partnership layer connects participants to fintechs, AI solution providers, data specialists, implementation partners and experienced operators. The purpose is targeted support for build, buy and partner decisions, not broad marketplace exposure.
The objective is not theoretical understanding. It is to help institutions leave with something they can test, challenge, govern or progress.
Outcomes
Every participating institution finishes with a decision package rather than a set of notes.
A shortlist of realistic AI use cases, with one selected priority case defined in enough detail to act on: the problem, the target segment, the data needed, the AI approach and the human decision points.
An initial governance and risk position covering accountability, approval logic, controls and escalation, so responsible AI is built into decision-making rather than discussed separately.
Pilot logic or an implementation pathway for the selected use case, including success metrics, so the next step is a decision rather than a further study.
A practical roadmap with sequencing and ownership, plus a shared institutional view of what AI means for the MSME agenda.
Stronger understanding of how AI supports MSME-focused financial services, and greater confidence in assessing feasibility, affordability and responsible adoption.
Clearer alignment on AI priorities linked to MSME service delivery, and a clearer path from solution design to real deployment for MSME clients.
Credible pilot-ready outputs across the cohort, and evidence that institutions are moving towards solutions that can reach MSMEs at scale.
Register your interest
Tell us which part of the programme fits your institution and we will come back with the structure, dates and what participation involves.
For institutions serving micro, small and medium-sized enterprises
Cohorts of five to ten institutions, each with a named sponsor
A three-month executive journey with a guided application phase
Every institution works on one live challenge of its own
We will respond with the full programme outline.
FAQs
Financial institutions serving micro, small and medium-sized enterprises. Within those institutions it is designed for CEOs and business heads, strategy and transformation leaders, senior risk, operations and product leaders, and the decision-makers who set institutional priorities and carry them through.
AI Foundations is a three-month executive journey with intensive in-person work at the start and the end and a guided application phase in between. The content runs across six themes, and each institution works on one live challenge of its own throughout.
No. Participants work on a live institutional challenge and submit outputs at agreed milestones. Each institution finishes with a prioritised use case, a governance baseline, pilot logic and a roadmap.
No. The programme is built for senior decision-makers. It develops judgement about where AI creates value, what responsible adoption requires and what to prioritise, not technical implementation skills.
A named sponsor, a nominated participant group, one clearly defined challenge, and the time to attend the sessions and submit outputs at the agreed milestones.
Each institution leaves with a decision package it can take into its own governance process: a prioritised use case, a governance and risk baseline, pilot logic and a six to twelve month roadmap.