NEVADA | PROFESSIONAL EXPERIENCE

Program Professional Framework

AI for Financial Planning & Analysis (AI-FP&A)

Program Overview

Artificial intelligence is reshaping how finance teams plan, forecast and explain performance. This programme shows FP&A professionals how to apply machine learning forecasting, driver-based models, anomaly detection and generative AI assistants to the planning cycle. Participants work with practical techniques such as time-series forecasting, regression on business drivers, automated variance commentary and scenario generation, using tools ranging from Python and Excel add-ins to AI features in planning platforms. Equal attention is given to data preparation, model validation, explainability, controls and the governance needed before AI outputs inform budgets and executive decisions in Gulf organisations.

Learning Outcomes

✓Prepare and clean historical financial and operational data for use in AI-based forecasting.
✓Build and compare a statistical and a machine learning forecast and evaluate accuracy using MAPE and bias measures.
✓Develop a driver-based model that links operational drivers to revenue and cost forecasts.
✓Use generative AI tools to draft variance commentary and management reports with appropriate human review.
✓Design controls and documentation for AI models used in planning and reporting.
✓Present AI-generated scenarios to decision makers with clear explanation of assumptions and limitations.

Target Audience

FP&A analysts and managers
Budgeting and forecasting specialists
Finance business partners
Finance transformation and systems leads

Detailed Program Modules

01AI in the FP&A Function

The planning cycle and where AI adds value
Machine learning, predictive analytics and generative AI
Current platforms and toolsets

02Data Foundations for AI Forecasting

Data sources, granularity and quality
Cleaning, feature engineering and calendars
Handling seasonality and Ramadan effects

03Forecasting Techniques

Time-series models and their limits
Regression and driver-based forecasting
Measuring forecast accuracy and bias

04Scenario Planning and Simulation

Automated scenario generation
Sensitivity and Monte Carlo analysis
Rolling forecasts with AI support

05Generative AI for Reporting and Insight

Automated variance commentary
Prompting for financial analysis
Reviewing and validating AI outputs

06Governance and Adoption

Model validation, explainability and controls
Data privacy and confidentiality
Building an AI-enabled FP&A roadmap

Training Methodology

Interactive expert-led sessions grounded in workplace examples

Case studies and practical exercises drawn from the region

Group workshops with peer review of decisions and deliverables

Formative feedback against clear performance criteria

Applied Project & Assessment

Applied Project

Participants build an AI-supported forecast for a revenue or cost line using provided or organisational data, compare it with the current forecast method, generate variance commentary with a generative AI tool and document the controls required for use in the next budget cycle.

Assessment

Short diagnostic at the start, practical tasks linked to each learning outcome, and evaluation of the applied project against published criteria.

University Certificate & International Accreditation

Professional Certificate accredited by City University Malaysia in AI for Financial Planning & Analysis (AI-FP&A)

International accreditation: International Auditors Group (IAG)