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AI Fundamentals in Financial Services

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Saïd Business School, University of Oxford

AI Fundamentals in Financial Services

This course is part of AI in Financial Services: Foundations through future trends Specialization

Instructor: Martin Schmalz

7,088 already enrolled

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4 modules

Gain insight into a topic and learn the fundamentals.

68 reviews

Beginner level

Recommended experience

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

97%

Most learners liked this course

4 modules

Gain insight into a topic and learn the fundamentals.

68 reviews

Beginner level

Recommended experience

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

97%

Most learners liked this course

What you'll learn

Understand the core technologies behind AI and the central role of data in training AI systems.
Explore how AI is applied in financial services through use cases such as fraud detection, credit scoring, customer service, and algorithmic trading.
Critically assess the risks, limitations, and ethical considerations involved in using AI within the financial sector.

Skills you'll gain

Tools you'll learn

Fraud detection

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

4 assignments¹

AI Graded see disclaimer

Taught in English

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Build your subject-matter expertise

This course is part of the AI in Financial Services: Foundations through future trends Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 4 modules in this course

Artificial Intelligence (AI) is rapidly reshaping the financial services landscape. From fraud detection and algorithmic trading to customer service chatbots and credit scoring, AI is at the heart of a new era in finance. This course is designed to give you a clear, practical understanding of how AI works, what it enables, and how it’s transforming the way financial institutions operate.

Through real-world examples, case studies, and engaging learning activities, you’ll gain insights into the key technologies that make AI possible, including machine learning, deep learning, and natural language processing, and see how they are applied across core functions in banking, fintech, and asset management. You’ll also explore how data drives these systems, the different learning methods AI uses, and the implications for strategy, governance, and ethics. Whether you’re a financial professional, policymaker, or simply curious about the future of finance, this course will equip you with the knowledge and confidence to engage in AI-related conversations and decision-making. No programming background is required, just an interest in how technology is shaping the future of financial services. By the end of the course, you will be able to: • Understand the foundational technologies that underpin Artificial Intelligence (AI), including Machine Learning, Natural Language Processing, and Deep Learning. • Explore the central role of data in powering AI systems, and the key learning methods used to train them. • Identify how AI is applied in financial services, including use cases such as fraud detection, credit scoring, customer service, and algorithmic trading. • Critically evaluate the risks, limitations, and ethical challenges associated with deploying AI in financial services. This course is the first in the AI in Financial Services: Foundations through Future Trends specialization. It provides the essential groundwork for understanding how AI works and why it matters in finance. After completing this course, we recommend continuing with 'Designing the Future of Finance' and 'Open Data and Intelligent Finance' courses to explore how AI intersects with Open Finance, embedded systems, and intelligent, ethical financial innovation.

Module details

This module provides a foundational introduction to Artificial Intelligence and its transformative role in financial services. It also offers an overview of the course structure, highlighting key topics and how each module will build your understanding. You'll explore key AI technologies: Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Robotics, and Expert Systems. These insights will prepare you to recognise how AI is reshaping financial operations, services, and decision-making processes.

What's included

4 videos7 readings1 assignment4 plugins

4 videosTotal 6 minutes

Welcome from Professor Martin Schmalz2 minutes
What is AI?2 minutes
How NLP powers language-based technology1 minute
How Expert Systems replicate human reasoning1 minute

7 readingsTotal 96 minutes

Your learning journey 15 minutes
Before you begin: reflect on your learning goals 10 minutes
Important note about course communication1 minute
Introducing AI in Financial Services10 minutes
What is Natural Language Processing (NLP)30 minutes
What are Expert Systems20 minutes
Conclusion: Inside the AI Toolbox10 minutes

1 assignmentTotal 20 minutes

Module quiz20 minutes

4 pluginsTotal 60 minutes

What is Machine Learning15 minutes
What is Deep Learning15 minutes
What is Computer Vision15 minutes
What is Robotics and Robotic Process Automation (RPA)15 minutes

This module explores the vital role of data in Artificial Intelligence and the different learning methods that AI systems use to generate insights and predictions. You’ll examine key data types, the characteristics of big data, and the core machine learning paradigms used in financial applications.

What's included

6 videos9 readings1 assignment4 plugins

6 videosTotal 10 minutes

Data: the fuel that powers AI 2 minutes
Challenges of working with large-scale data in finance1 minute
Comparing traditional computing and AI3 minutes
Supervised Learning: a loan repayment example1 minute
Unsupervised Learning: a segmentation example1 minute
Reinforcement Learning: a customer engagement example1 minute

9 readingsTotal 100 minutes

Introduction10 minutes
Conclusion and reflection20 minutes
Traditional computing approaches 15 minutes
Artificial Intelligence approaches 10 minutes
Comparing traditional computing and AI - summary10 minutes
Conclusion and reflection20 minutes
Supervised Learning5 minutes
Unsupervised Learning 5 minutes
Reinforcement Learning5 minutes

1 assignmentTotal 20 minutes

Module quiz20 minutes

4 pluginsTotal 70 minutes

Data Paradigms and Data Types 20 minutes
Challenges of collecting, managing and using large data sets 15 minutes
Choose the right computing approach 15 minutes
Which type of learning is it? 20 minutes

This module demonstrates how AI is applied across four core areas of financial services: fraud detection, credit scoring, customer service, and algorithmic trading. You’ll explore real-world use cases to understand how AI adds value, the models and data behind it, and the challenges institutions face when deploying these technologies.

What's included

5 videos9 readings1 assignment4 plugins

5 videosTotal 6 minutes

Applying AI in Financial Services2 minutes
How AI enhances fraud detection1 minute
Why credit scoring needs a rethink1 minute
Personalisation and the future of customer service1 minute
AI at speed - the rise of algorithmic trading1 minute

9 readingsTotal 175 minutes

Reflect on your own experience 15 minutes
How AI-based fraud detection works 20 minutes
Real-world examples of AI-based fraud detection 20 minutes
How AI models assess credit risk 20 minutes
Real-world examples of AI credit scoring 20 minutes
How chatbots are driving increased personalisation 20 minutes
Real-world examples of AI driven personalisation in finance 20 minutes
How Algorithmic Trading works 20 minutes
Real-world examples of AI in Algorithmic Trading 20 minutes

1 assignmentTotal 20 minutes

Module quiz20 minutes

4 pluginsTotal 60 minutes

Challenges and considerations for AI-based fraud detection 15 minutes
Challenges and considerations for AI-based credit scoring 15 minutes
Challenges and considerations for chatbots in finance 15 minutes
Challenges and considerations for AI in Algorithmic Trading 15 minutes

In this final module, you’ll consolidate your learning and apply your knowledge through a peer-reviewed written assignment. You’ll reflect on key concepts, revisit course highlights, and explore the real-world implications of AI in financial services.