Machine Learning in Banking and Finance Masterclass
What machine learning can and cannot do for banking and risk — supervised and unsupervised methods, alternative data and explainable AI, worked in practice.
Format
Classroom · Live Virtual
Upcoming sessions
Pick a session to applyADMISSIONS OPENThe programme
Machine learning has moved deep into banking, risk management and modelling — but adoption without interrogation swaps one model risk for another. This intensive course examines what the advances actually offer financial institutions, and where the limitations sit. Working from practical examples and use cases, participants build command of supervised and unsupervised learning, sequential and deep learning, alternative data, and the metrics of explainability and interpretability for AI models. Behavioural and quantitative finance applications are developed — including investment strategies with ML and graphical ML — and a practical case study lets the cohort apply the theory to real-world examples, including conducting AI responsibly without reinforcing existing bias.
What you will do
Who attends
- Risk management and quantitative analytics teams
- Data science and machine learning practitioners
- Portfolio management and financial engineering professionals
- IT teams supporting model platforms
Programme agenda
Built for the decisions no textbook prepares you for
I.ML foundations for finance
- Supervised and unsupervised learning
- Recent advances in sequential and deep learning
- Opportunities and limitations for financial institutions
II.Data and explainability
- Alternative data: promise and pitfalls
- Metrics of explainability and interpretability
- Implications for finance and regulatory compliance
III.Applications
- Behavioural and quantitative finance use cases
- Investment strategies with ML and graphical ML
- Automation and the efficiency of the finance function
IV.Responsible adoption
- Interrogating models and partnering with data science
- Avoiding reinforced bias
- Threats, threat actors and vulnerabilities
- Practical case study of ML use cases
Frequently asked
Do these programmes cover the Basel III final reforms and the ICAAP/ILAAP cycle?
Yes. The BIZENIUS banking curriculum is built around the Basel III endgame, ICAAP, ILAAP, IRRBB, IFRS 9 provisioning, stress testing and BCBS 239. Participants leave able to quantify the output floor on their own portfolios, write capital and liquidity documents that withstand supervisory review, and defend the numbers to their board.
Are the programmes adapted to regional supervisors such as SAMA, CBUAE or BCEAO?
Casework is built around supervisory documents rather than textbook theory, and faculty include former practitioners who have sat on both sides of an examination. Programmes address the questions SAMA, CBUAE, BCEAO and other home regulators actually put to the desk, and an in-house edition can be tailored to a single jurisdiction.
How do I secure a seat on a banking programme?
Apply for a seat or request the brochure from the programme page. A senior practitioner — not a sales team — responds within one business day, and the brochure arrives with that reply. BIZENIUS runs on enquiry: there is no online checkout.
Can a programme run in-house for our bank?
Every BIZENIUS programme can be delivered in-house, tailored to your balance sheet, your regulator and your data, in English or French. Many institutions start with an open cohort, then commission a private edition for the wider team.
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In their words
Knowledge transfer, emphasised throughout
“We worked with BIZENIUS for our Fresh Graduates Programme — they are simply amazing. Knowledge transfer and practical learning were emphasised throughout.”
Kuwait Investment Authority
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The Capability Arc™
Fix it · Advisory
Advisory & Consultancy
A senior bench across risk, treasury and regulation.
Learning is one point on the Capability Arc. Many institutions pair this programme with the advisory engagement — and automate what the framework demands.
Teams from these institutions train with BIZENIUS
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Take the brochure with you.
One request — the full agenda, the faculty and the next cohort dates, sent personally by the admissions team.