AI in Project Finance: Understanding, Model Building, and Analysis

Available Dates & Locations

Dates

September 7, 2026

–

September 11, 2026

Location

kuala Lumpur

Duration

5 Days

Venue

09:00 am – 03:30 pm (Kuala Lumpur)

Language

Fees

$5,950.00

COURSE OVERVIEW

This program offers a rigorous and practical exploration of how Artificial Intelligence is reshaping project finance across different industries. Participants will master the foundations of AI, learn how financial datasets are prepared for modeling, and build AI-driven tools that enhance forecasting, credit assessment, and investment decision-making. Through hands-on exercises, real case applications, and structured guidance, learners gain the ability to design, evaluate, and deploy AI models that meet the analytical needs of modern project finance teams. The course further emphasizes governance, transparency, and responsible AI usage to ensure reliable and defensible financial outcomes.

COURSE OBJECTIVES

By attending this course, participants will be able to:

Apply AI concepts within project finance environments
Build predictive financial models using appropriate AI techniques
Analyze project risks through machine learning insights
Evaluate model accuracy and interpret predictive outputs
Integrate AI-generated forecasts into investment decisions
Design clean and structured datasets for financial modeling
Implement governance controls for AI-supported analysis
Translate AI model results into actionable recommendations

TARGET COMPETENCIES

AI Foundations
Project Finance Principles
Data Preparation Techniques
AI Model Building
Financial Analysis Automation
AI Governance

This course is designed for project finance analysts, investment professionals, corporate finance teams, project managers, consultants, bankers, financial modelers, and public-sector specialists involved in evaluating or managing complex capital projects. It is also suitable for professionals seeking to strengthen their analytical capabilities using AI-driven methods, individuals transitioning into roles involving predictive financial modeling, and teams responsible for strategic investment assessments, credit decisions, and long-term project viability analysis.

The course employs interactive lectures, hands-on AI model development, real financial datasets, group problem-solving, practical simulations, and case-based analysis to ensure deep understanding and immediate applicability in professional settings.

AI Foundations

Core AI concepts relevant to finance
Understanding machine learning types
Model accuracy and performance basics
Ethical and responsible AI considerations
Interpreting predictive financial outputs

Project Finance Principles

Structure and components of project finance
Capital budgeting and investment evaluation
Debt–equity mix and lender expectations
Cash flow modeling structure and logic
Sensitivity and scenario planning

Data Preparation Techniques

Collecting and organizing financial datasets
Cleaning and transforming raw project data
Feature engineering essentials for modeling
Managing outliers and inconsistencies
Preparing time-series data for training

AI Model Building

Selecting appropriate model types
Training and validating financial models
Understanding hyperparameters
Evaluating performance metrics
Preparing models for deployment

Financial Analysis Automation

Automated forecasting and projections
AI-driven sensitivity testing
Pattern recognition in project data
Automated covenant monitoring
Real-time variance alerts

AI Governance

Governance frameworks for AI models
Model risk management controls
Data privacy and compliance
Transparency and explainability
Model documentation and auditability