Generative AI for Financial Services
Deploy language models in a regulated institution without betting the licence.
The executive challenge
The problem this program solves
Your competitors have industrialised their generative ai capability into pricing, service and operations while your organisation still debates the pilot. Every quarter of hesitation now compounds. The talent you hired leaves, the data you hold decays, and the gap between your generative ai ambition and your capability widens every quarter. This is where generative ai stops being a technology conversation and becomes an executive discipline you can defend in any boardroom.
Context
Why this matters now
Capability
What you will be able to do
- Evaluate where generative ai creates economic value across the organisation — and where it reliably does not.
- Read generative ai evidence — dashboards, model outputs, vendor claims — and know exactly what to trust.
- Construct a generative ai roadmap sequenced by value, feasibility and risk.
- Defend a generative ai investment case before a board that has been disappointed before.
The IPAT Course Standard
The five-day journey
Each day is a deliberate progression in managerial capability — from strategic context, to analytical frameworks, to applied practice, to executive judgement under pressure, to a capstone that produces something your organisation keeps.
IPAT Signature Case™
The Generative AI Model Nobody Can Explain
A a national revenue authority deployed a generative ai model into daily operations. It performs — until a customer dispute, a journalist and the regulator arrive in the same week, and no one can reconstruct why the model decided what it decided.
Your decision: Pause the model pending an explainability rebuild, defend it as deployed, or restrict it to advisory use — each response signals something different to the regulator, the market and your own staff.
IPAT Data Lab™
Three functions at a fast-scaling e-commerce platform report three different truths about the same generative ai question.
Dataset: Synthetic multi-source generative ai dataset — finance, operations and customer tables that disagree.
Your task: Reconcile the sources, build the single defensible view, and decide which dashboard the executive committee keeps.
A reconciled generative ai decision view and the data architecture behind it.
Data → Analysis → Decision, not Data → Code → Certificate
Day 5 · The Capstone
What will you change when you return to work?
Build a twelve-month analytical and AI roadmap for your organisation: the value case, the data foundations, the governance, and the first 90 days.
Methodology
Frameworks you will master
- • IPAT Data-to-Decision Framework™
- • IPAT Executive Capability Model™
- • Value-versus-feasibility portfolio analysis
- • CRISP-DM analytical lifecycle
- • Model risk management principles (SR 11-7 adapted)
Cohorts
Upcoming cohorts
New dates are being scheduled
Register with your preferred start date and our admissions team will match you to the next available cohort — or contact us to arrange an in-house delivery for your organisation.
Register your interestExplore further
Related programmes
Learners of Generative AI for Financial Services frequently pair it with these offerings from the same divisions.
