AI Prompting for Sustainable Finance Skills for Credible & Ethical Use - Digital Banking

This one-day applied programme equips banking professionals with structured AI prompting techniques for responsible use in sustainable finance workflows.

It is not a technical coding session, but a commercially focused programme that strengthens advisory capability through extractive discipline, citation control, and structured analytical prompting.

The programme emphasizes disciplined extractive methodologies over open-ended generative use to reduce hallucination risk, model drift, and regulatory exposure. It clarifies where AI can enhance competitive positioning and where governance safeguards must apply.

Through practical simulations, participants learn both the opportunities and boundaries of AI application in banking environments. All case materials are developed strictly for training purposes and do not constitute financial, legal, regulatory, or investment advice. Participants remain responsible for independent professional judgement and compliance with institutional policies.

At its core, the programme positions AI as an analytical co-pilot—enhancing banker expertise while preserving accountability and sound credit discipline.

Programme Outline

Learning Objectives

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

Explain governance boundaries, confidentiality requirements, and practical “Do’s and Don’ts” when applying AI in banking environments
Apply structured multi-step AI prompting techniques to extract material from sustainability disclosures
Differentiate and implement extractive and generative prompting modes, including citation control techniques, to reduce hallucination and documentation risk
Apply AI prompting techniques to support sustainable finance advisory discussions within appropriate governance safeguards
Evaluate AI-generated outputs for assumptions, data quality limitations, and governance considerations before advisory use

Programme Outline

Module 1: Responsible AI in Banking – Guardrails Before Use
AI Risk Landscape in Financial Institutions
Data Governance & Confidentiality
Professional Accountability
Activity
Module 2: Applied Simulation on Structured Extraction
Topic Coverage with simulation case practice

Structured discovery prompting
Controlled extractive prompting
Output constraint design
Citation enforcement techniques
Thematic classification (ESG alignment)
Analytical reasoning prompting (gap analysis)
Validation prompting (assumption detection)
Module 3: Applied Advisory Persona Simulation
Topic Coverage & Simulation Cases practice

Persona prompting in advisory context
Module 4: Limitation
Golden Rules in apply Ai Prompting
Human in the Loop" Mantra
How AI can support but never replace financial responsibility
Module 5: Emerging Tools
Intro to AI agents & Retrieval-Augmented Generation (RAG) for ESG
Demo: Compare traditional ESG scoring vs RAG-enhanced AI agent output

METHODOLOGY

Case Studies, Hands-on AI Simulations, Interactive Lecture

All case materials, prompts, and product structuring exercises are developed strictly for training and capability-building purposes. The programme does not constitute financial, legal, regulatory, or investment advice, and participants remain responsible for independent professional judgement, internal approvals, and compliance with their institution’s policies and applicable regulations.

Participant profile

Financial Institution Professionals (Relationship Managers, Credit/Risk Officers, Sustainability Teams)
Regulators and Policymakers
Fintech Developers and ESG Data Analysts
Sustainable Finance Product Developers

Trainer

Ng Keng Fai

Lead Trainer and Data Science Lead, Growth.Pro Data Science Consulting & Training

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Ng Keng Fai

Lead Trainer and Data Science Lead, Growth.Pro Data Science Consulting & Training

Keng Fai is the Lead Trainer and Data Science Lead at Growth.Pro Data Science Consulting & Training, where he designs interactive corporate training programs in AI, data science, and machine learning. He also develops frameworks and prototypes for AI-driven solutions, helping businesses integrate cutting-edge technology into their operations.

With a diverse background spanning academia, entrepreneurship, and industry, Keng Fai has previously lectured at UniRazak and served as a vocational trainer at New Era Institute of Vocational and Continuous Education (Kajang). He also founded and led software development teams in fintech and edtech startups, combining his expertise in marketing, software engineering, and AI to deliver impactful solutions.

Keng Fai also brings corporate training experience across manufacturing, fintech, and financial institutions, equipping professionals with future-ready AI and data competencies. He has led specialized workshops and upskilling programs for manufacturing giants, trained fintech teams on AI-powered automation and fraud detection and conducted analytics and AI strategy sessions for banks and financial service providers.
His cross-industry experience includes robotics/mechatronics engineering, with roles in oil & gas and manufacturing at Flextronics. Additionally, he has consulted for and coached clients such as Beyond Insights, Plus Minus Zero, and Watson-Marlow, helping them leverage AI and data-driven strategies.

During the Malaysian Movement Control Order (MCO), Keng Fai conducted e-training sessions for entrepreneurs across industries, covering marketing, web development, and data analytics for clients like TOC Automotive College and La Gourmet. His expertise also earned him an invitation to Astro AEC’s《企业棒帮忙》SME Great Helper, where he advised on digital transformation for the music industry.

Core Strengths:

Cross-industry expertise (marketing, manufacturing, fintech, e-learning, financial services)
Hands-on, experiential training in AI & data science
Proven track record in corporate training, AI prototyping, and digital transformation