NUS
 
ISS
 

Financial Models & Analytics

Building strong foundations in financial white box modelling 

Overview

Part of Graduate Certificate in Intelligent Financial and Risk Management
Duration 3 days
Course Time
Enquiry Please contact ask-iss@nus.edu.sg for more details.
This course prepares aspiring individuals aiming to build a strong foundation in financial modelling, focusing specifically on risk and pricing analytics. As a learner, you will by understanding how major financial institutions operate and then rapidly advance to applying white-box Machine Learning (ML) models (models which internal mechanisms are completely transparent, interpretable) and aligned with regulatory expectations. To ensure you stay ahead of the curve, you will also be exposed to the absolute latest, cutting-edge advancements in artificial intelligence. Discover how AI Agents and low-code Agentic IDEs can assist you in building, refining, and deploying sophisticated ML analytics to solve real-world, high-stakes business problems in the financial sector. 

Key Takeaways

By the end of the course, participants will be able to:

  • Decode the Financial Ecosystem: Interpret the core business domain of diverse financial institutions, identify their most pressing challenges, and engineer precise analytical solutions to resolve them.
  • Master Governance & Compliance: Evaluate the structural importance of pricing and risk models, aligning them securely with key international and local regulatory frameworks (such as Basel and Singapore's MAS FEAT principles).
  • Build Transparent Models: Develop, run, and scale highly interpretable white-box models on cloud platforms tailored specifically to financial service applications.
  • Harness Next-Gen AI: Fully appreciate and leverage Generative AI, autonomous AI Agents, and low-code developer tools to accelerate and optimise your financial problem-solving workflows. 



Who Should Attend

This course is designed for aspiring data analysts and data scientists who wish to build a career in the finance industry. It is also highly relevant for existing professionals in financial services who want to strengthen their foundation in understanding the operating model of FIs, their problems faced and applying the appropriate analytics to solve them. 

This includes:

  • Aspiring Data Analysts & Data Scientists looking to kickstart a rewarding, high-growth career in the financial services sector.
  • Existing Financial Services Professionals who want to strengthen their core foundation in financial institution operations and learn how to apply modern analytics to solve business problems.
  • Quantitative & Risk Management Professionals wanting to adopt modern white-box ML and cloud technologies.
  • Fintech & Regtech Developers/Consultants seeking to understand model governance, API data sourcing, and AI agent integration.
  • Technical Professionals seeking a practical path to enhance their machine learning capabilities. 

Pre-requisitesA basic, introductory knowledge of a programming language (e.g., Python) is helpful to get the most out of the hands-on sessions, but it is not mandatory.


What to Bring

No printed copies of course materials are issued.
Participants must bring their internet-enabled computing device (laptops, tablet etc) with power charger to access and download course materials.

If you are bringing a laptop, please see below for the tech specs:

Minimum

Recommended

Operating Systems

• Windows 7, 8, 10 or
• Mac OS

Laptop running the latest
version of either Windows or
Mac OS

System Type

32-bit

64-bit

Memory

8 GB RAM

16+ GB RAM

Hard Drive

256 GB disk size

Others

• An internet connection – broadband wired or wireless
• Installation permissions (non-company laptops) 
• Keyboard
• Mouse/Trackpad
• Display
• Power adapter (laptop battery might run out)

DirectX 10 graphics card for graphics hardware acceleration





What Will Be Covered

  • Develop a conceptual understanding of how various financial institutions operate
  • Connect business drivers with relevant analytics such as risk assessment, fraud detection, pricing, customer analytics, and regulatory reporting
  • Evaluate and leverage appropriate types of analytics to solve FI related problems
  • Implement Financial Model Building Fundamentals by appreciating the importance of building a good financial model with sourcing relevant financial data via APIs, source pricing model inputs, hyper-parameters and back testing models
  • Appreciate the importance of governance & regulatory frameworks in building models (e.g., Basel, MAS FEAT)
  • Building/Utilising White-Box models with specific financial applications; understand white-box modelling in a cloud platform and apply them to portfolio optimisation, customer insights, fraud detection, crypto currency price prediction, customer loan approvals
  • Appreciate the use of Generative AI, AI Agents & related tools by understanding how to leverage Generative AI tools, Agentic IDEs, Model Context Protocols to assist in financial model building



Fees & Subsidies

SkillsFuture Singapore (SSG) Funding 2026 (Effective 1 July)

Fee ComponentFull Course FeesSingapore Citizens & PRs Aged 21 Years and Above (70% Funding Support)Singapore Citizens Aged 40 Years and Above (90% Funding Support)Enhanced Training Support for SMEs (ETSS) (90% Funding Support)
Full Course FeeS$2,850.00S$2,850.00S$2,850.00S$2,850.00
SSG Funding-S$1,995.00S$1,995.00S$1,995.00
Nett Course FeeS$2,850.00S$855.00S$855.00S$855.00
9% GST on Nett Course FeeS$256.50S$76.95S$76.95S$76.95
Additional Funding if Eligible Under Various Schemes--S$570.00S$570.00
Total Nett Course Fee Payable, Including GSTS$3,106.50S$931.95S$361.95S$361.95

 

Note:

  1. SSG Funding is available to qualified individuals, subject to meeting the attendance requirement and passing of assessment.
  2. All self-sponsored Singaporeans aged 25 and above can use their SkillsFuture Credit to pay for course fees. For more information about SkillsFuture Credit, click here.
  3. SME fees are applicable only to participants who are sponsored by small and medium enterprises.
  4. SSG funding is subjected to availability.



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Certificate

The ISS Certificate of Completion will be issued to participants who have attended at least 75% of the course and pass the required assessments.



Preparing for Your Course

NUS-ISS Course Registration Terms and Conditions

Find out more.

NUS-ISS and Learner’s Commitment and Responsibilities

Find out more.

WIFI Access

WIFI access will be made available to participants.

Venue

NUS-ISS
25 Heng Mui Keng Terrace
Singapore 119615

Click HERE for directions to NUS-ISS

In the event of a change of venue, participants are advised to refer to the acceptance email sent one week prior to the commencement date.

Course Confirmation

All classes are subject to confirmation and NUS-ISS will send an acceptance email to participants one week prior to the commencement date. Confirmed registrants are to attend and complete all lectures, class exercises, workshops and assessments (where applicable). Additionally, all responses to feedbacks and surveys conducted by NUS-ISS and its partners must be submitted. All training and assessments will be delivered as described in the course webpage.

General Enquiry

Please feel free to write to ask-iss@nus.edu.sg if you have any enquiry or feedback.




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