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AI Fundamentals in Financial Services

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AI Fundamentals in Financial Services

7,870 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.8

79 reviews

Beginner level

Recommended experience

Flexible schedule
1 week at 10 hours a week
Learn at your own pace

Gain insight into a topic and learn the fundamentals.
4.8

79 reviews

Beginner level

Recommended experience

Flexible schedule
1 week at 10 hours a week
Learn at your own pace

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.

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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.

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.

What's included

1 video4 readings1 assignment1 peer review

1 videoTotal 2 minutes
  • Summary2 minutes
4 readingsTotal 55 minutes
  • Key takeaways and reflection15 minutes
  • Bibliography and further reading10 minutes
  • Written assignment information20 minutes
  • Next steps10 minutes
1 assignmentTotal 40 minutes
  • Course quiz40 minutes
1 peer reviewTotal 120 minutes
  • Written assignment submission120 minutes

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Instructor

Instructor ratings
4.6 (25 ratings)
Saïd Business School, University of Oxford
1 Course7,870 learners

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Showing 3 of 79

AN
·

Reviewed on Jan 4, 2026

Very good introduction for AI in Financial services. Excellent way of teaching and quizzes

JC
·

Reviewed on Jun 1, 2026

Excellent beginners course in AI and its applications in Finance.

NE
·

Reviewed on Dec 6, 2025

I really enjoyed this course, interesting yet knowledgeable

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