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Young Talent Programme for AI in Finance (YTP-AIF) |
The Young Talent Programme for AI in Finance (“YTP-AIF”) is launched by the Institute of Banking and Finance (IBF), with support from the Monetary Authority of Singapore. This pilot programme aims to build a pipeline of young talent for an
AI-enabled financial sector and strengthen the education-to-work pathways by integrating structured industry exposure into formal studies.
The programme is designed to equip participants with applied AI and financial sector skills
that are in-demand, through structured industry exposure and hands-on learning on real-world problem statements, to support transitions into roles with AI application.
Stage 1: Foundational Masterclass | (A one-week intensive masterclasses followed by four weekly classes) Equip participants with a foundational understanding of AI and how AI can be applied responsibly within the financial sector. |
Stage 2: Applied Learning | (8-10 weeks) Participants to work on projects linked to industry problem statements, with industry mentorship and leveraging AI tools and synthetic data. |
Stage 3: Project Presentation | Presentation to participating financial institutions (FIs). |
Stage 4: Progression Opportunities | Selected participants to be offered internship, traineeship or full-time opportunities. |
This bootcamp equips students with both foundational knowledge in AI and financial services, as well as practical industry-relevant skills through hands-on learning and project work. Students gain a clearer understanding of how AI is applied in
the sector, work on real-world business problem statements, and learn from both academic and industry partners.
Future-ready skills • Applied AI and in-demand financial sector skills, with industry insights from practitioners |
Industry Exposure • Hands on learning through real-word problem statements • Potential longer internships / post-graduate traineeship opportunities with participating FIs |
Mentorship • Learn from industry practitioners • Build professional networks and connections |
This programme is open to all Year 2 to Year 4 undergraduate students (in the academic year starting August 2026) from all disciplines (both tech and non-tech) across all autonomous universities.
Applicants should ideally:
The curriculum combines AI fundamentals, financial sector context, and practical application topics.
Pillar 1 | Pillar 2 | Pillar 3 |
of AI and Financial Data Literacy, Prompt Engineering and Explainability, AI Prototype Development, Financial Services AI Requirements | AI Ethics and Risk Management, Data Governance for AI, AI Security and Auditability | AI in Risk Management, AI in Sales, Marketing, Pricing, and Consumer Analytics, AI in Technology and Operations, AI to Support Regulatory Compliance, AI in Investment Research |
*Students will only take one module most closely associated with their project
Note: Curriculum and schedule are subject to changes
Module Synopsis |
| 19 May - 15 Jun 2026 | Application period |
| 15 Jun - Mid Jul 2026 | Application review |
| Mid - End Jul 2026 | Enrolment / Onboarding *Only successful applicants will be notified |
| Aug - Sep 2026 | Stage 1: Foundational Masterclass |
| Sep - Nov 2026 | Stage 2: Applied Learning |
| Nov 2026 | Stage 3: Project Presentation |
IBF has brought together key financial institutions, institutes of higher learning and technology partners to co-develop and deliver the programme.

1. Will all students be offered internship or traineeship opportunities?Participants will present their projects to participating financial institutions, which will take these presentations into consideration when assessing students for internship or traineeship opportunities. |
2. Will I be guaranteed a placement with the FI after I complete the internship or traineeship?Opportunities will depend on students’ performance during the programme and the hiring needs of financial institutions. |
3. Is the programme credit-bearing?Singapore Management University (SMU) and Nanyang Technological University (NTU) will conduct the masterclass and applied learning components and provide academic credit recognition for their students who participate.Students from National University of Singapore (NUS), Singapore Institute of Technology (SIT), Singapore University of Social Sciences (SUSS), and Singapore University of Technology and Design (SUTD) may participate, though academic credit recognition will not apply in the pilot run. |
4. How will I be informed of the outcome of my registration?Applicants will be notified of the registration outcome via the email provided in the application form after the applications have been processed. |
5. What happens if I drop out from the programme?Withdrawals will be subject to the policies of the university delivering the course. Students are advised to check with their universities on the relevant procedures.SMU contact: Randall Eugene DURAN [email protected] [For curriculum -related matters] Emmaline LIM [email protected] [For programme admin matters] NTU contact: [email protected] |
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