AI in Financial Services

AI in Financial Services

Introduction

Artificial Intelligence (AI) is becoming a foundational capability in finance and banking. Financial institutions are increasingly using AI to enhance risk management, fraud detection, financial analysis, customer engagement, reporting, and operational efficiency. With the rise of Large Language Models (LLMs) and Generative AI, finance professionals now have access to powerful tools that can analyse information, generate insights, and support decision-making at unprecedented speed.

However, the finance and banking sector operates in a highly regulated environment, where data confidentiality, explainability, accountability, and ethical use are critical. AI systems must therefore be understood, governed, and applied responsibly, rather than used blindly.

This course provides a practical, business-oriented introduction to AI for finance and banking professionals. Participants will learn core AI concepts, explore leading AI tools such as ChatGPT, Gemini, Copilot, Perplexity, Grok, Claude, Manus, DeepSeek, Qwen, and NotebookLM, and apply them hands-on to real financial workflows. The focus is on practical application, compliance awareness, productivity improvement, and strategic readiness, without requiring any programming background.

Who Should Attend

This course is designed for working adults and professionals, including:

Banking and financial services professionals
Finance managers, analysts, and executives
Risk management, compliance, audit, and AML teams
Credit, lending, and investment professionals
Operations and customer service managers
Digital transformation and innovation teams
Business leaders responsible for AI adoption in finance

Level: Beginner to Intermediate. No prior AI or technical background is required
Delivery Mode: 2-days, In-house. Instructor-led, hands-on AI tools (no coding required)

Outcome

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

Understand key AI concepts and terminology relevant to finance and banking.
Clearly distinguish between AI, Machine Learning, Deep Learning, LLMs, and Generative AI.
Evaluate and select appropriate AI tools for financial and banking tasks.
Apply AI tools to financial analysis, reporting, documentation, and communication
Use AI responsibly within regulatory, ethical, and organisational boundaries
Identify and prioritise AI use cases relevant to their own organisations
Contribute meaningfully to AI adoption and strategy discussions in finance teams

Select to design your own content and request for a customized quotation

No	Topic	Topic Description
1	Understanding AI in Finance and Banking	Overview of AI adoption trends in finance and banking What is Artificial Intelligence? Relationship between AI, Machine Learning, and Deep Learning Introduction to Large Language Models and Generative AI How AI systems learn, predict, and generate outputs Key AI use cases in finance and banking: fraud detection and monitoring credit scoring and loan assessment risk analytics and reporting customer service and virtual assistants Strengths and limitations of AI in regulated environments
2	AI Tools Landscape for Finance Professionals	Overview of leading AI tools for finance: ChatGPT, Gemini, Copilot, Claude Perplexity, Grok, Manus, DeepSeek, Qwen, NotebookLM Comparing tools by: capabilities and limitations accuracy, reasoning, and reliability data privacy and confidentiality considerations Selecting the right AI tool for: financial research and analysis reporting and documentation internal communication and customer-facing responses Fundamentals of prompt engineering for finance professionals Hands-on activities Writing structured prompts for financial tasks Comparing AI-generated outputs across multiple tools Identifying errors, bias, and compliance risks
3	AI for Financial Analysis and Business Reporting	Using AI to support financial statement analysis Identifying trends, risks, and anomalies with AI AI-assisted management and board reporting Working with spreadsheets using AI assistants: Excel with Copilot Google Sheets with Gemini Converting numerical outputs into business narratives Hands-on activities Generating financial insights from sample datasets Drafting executive-ready summaries using AI
4	Responsible AI, Ethics, and Compliance in Finance	Key risks of AI usage in finance: hallucinations and incorrect outputs bias, fairness, and discrimination over-reliance on AI-generated content Regulatory and compliance considerations: data protection and confidentiality explainability and audit requirements Human-in-the-loop decision-making models Best practices for responsible and compliant AI use
5	AI for Risk Management, Fraud, and Credit Support	Role of AI in fraud detection and transaction monitoring AI-assisted AML documentation and reporting Supporting credit risk analysis using AI tools Generating risk narratives and explanations with AI Understanding AI limitations in regulated decision-making Hands-on activities Analysing risk and fraud scenarios using AI Drafting credit and risk assessment narratives
6	AI for Customer Experience and Banking Operations	AI chatbots and virtual assistants in banking AI for handling customer inquiries and FAQs Using AI to explain banking products, policies, and procedures Knowledge-based AI using internal documents: NotebookLM and Manus Improving operational efficiency with AI Hands-on activities Designing an AI-assisted banking FAQ Enhancing customer communication using AI
7	AI-Enabled Workflow Automation in Finance	Designing AI-supported workflows in finance: documents → analysis → reports Integrating AI tools into daily finance operations Managing risks in semi-automated workflows Measuring productivity, quality, and return on investment Exercise Designing an AI-supported finance workflow
8	AI Strategy for Finance Leaders and Decision-Makers	Identifying high-value AI opportunities in finance departments Build versus buy versus partner decisions Developing an AI adoption roadmap Establishing internal AI policies, governance, and controls Preparing finance teams for AI-enabled roles and future skills Workshop Drafting a high-level AI strategy for a finance or banking unit

Expert

Dr. Mohammed Muayad Abdulrazzaq

Dr. Mohammed Muayad Abdulrazzaq, fondly known as Dr. Obay is an accomplished AI Trainer, Academic Leader, TEDx Speaker, Industry Advisor, and Entrepreneur, internationally recognised for his contributions to Artificial Intelligence education, research, and innovation. Holding a Ph.D. in Artificial Intelligence and bringing over 20 years of experience across the information technology landscape, Dr. Obay’s expertise spans AI, Big Data Science, Machine Learning, Deep Learning, Generative AI, Large Language Models (LLMs), and Immersive Technologies. As a certified and HRD Corp-accredited trainer, Dr. Obay has trained more than 5,000 professionals, students, and business leaders through highly practical and results- driven programs in Data Science, AI Engineering, Generative AI, and LLMs. His workshops are widely praised for their clarity, relevance, and ability to translate complex AI concepts into real-world business impact. Recently, Dr. Obay was honoured to begin a new chapter as an Industry Advisor at ICMS, contributing to advanced programs and professional certifications in Generative AI, Large Language Models, Google AI & Machine Learning, and Microsoft Azure AI. His advisory role bridges academia and industry by empowering future-ready talent and organisations to thrive in the era of intelligent automation. Recognised for his excellence in AI education and leadership, Dr. Obay serves as an ELITE Fellow at the University of Malaya (UM) — Malaysia’s top-ranked university — and as an Adjunct Associate Professor at Taylor’s University, where he supervises Ph.D. and Master’s students at Taylor’s University and the International Islamic University Malaysia (IIUM). His academic work focuses on applying AI to solve real- world problems while shaping the next generation of innovators. An entrepreneur at heart, he is the Founder of Artificial Intelligence & Coding for All (AIC4ALL) — a global learning platform that equips learners of all ages with essential skills in AI, coding, and data science for IR 4.0 & IR 5.0. He also leads INNOEYETIVE, a digital innovation agency leveraging AI, Big Data, and Immersive Tech to accelerate digital transformation. As a TEDx and international speaker, Dr. Obay has delivered impactful talks and keynotes that demystify AI, inspire innovation, and promote ethical adoption of emerging technologies. His lifelong mission is simple yet powerful — to empower professionals, educators, and leaders worldwide to harness the transformative power of AI for a better, smarter future.