Generative AI for Finance: Use Cases, Applications and Regulation (online)



Overview

This course delves into the transformative potential of generative AI (GenAI) and large language models (LLMs) in the financial sector. Tailored for professionals but also people new to this exciting area who are eager to thrive in an AI-driven landscape, it offers a comprehensive understanding of how these cutting-edge technologies are revolutionising financial services.

Participants will gain hands-on experience with prompt engineering to optimise AI functionality for a variety of financial tasks. Through real-world use cases, the course demonstrates how financial institutions are leveraging GenAI and LLMs for portfolio management, risk assessment and predictive analytics.

Beyond technical applications, the course examines the critical regulatory and ethical frameworks governing AI in finance. You’ll learn to navigate compliance requirements, address data privacy concerns and implement ethical AI practices in decision-making processes. The course also features a guest lecturer, legal expert Claudia Otto, who will introduce GenAI's legal implications and its role in shaping financial regulations.

Dates, Times and Delivery 

This course runs over two weeks, from 20 - 30 April 2026, with online sessions delivered via Microsoft Teams.

Sessions will be held on Mondays and Thursdays from 7.00 - 8.30pm (UK time) on:

  • Monday, 20 April

  • Thursday, 23 April

  • Monday, 27 April

  • Thursday, 30 April

A world clock, and time zone converter can be found here: https://bit.ly/3bSPu6D 

This is a ‘virtual classroom’ course. 

To replicate the experience of a classroom, the sessions are ‘live’ and are not recorded. 

No in-person attendance at Oxford is required and you do not need to purchase any software.

Accessing Your Online Course 

Details about accessing the private MS Teams course site will be emailed to you during the week prior to the course commencing.  

If you have not received your joining instructions three working days before the course start date, please get in touch. 

Programme details

Session 1: Introduction to AI, GenAI and LLMs in finance

  • Overview of AI in financial services
  • Key concepts of generative AI (GenAI)
  • Understanding large language models (LLMs) and their capabilities
  • Trends and innovations in AI for finance (shaping the competitive landscape)

Session 2: Fundamentals of prompt engineering for financial use cases

  • What is prompt engineering?
  • Crafting effective prompts for financial tasks
  • Addressing challenges in prompt design
  • Hands-on examples of prompts in real-world applications

Session 3: Ethical and regulatory considerations in GenAI for finance (with guest lecturer Claudia Otto)

  • Risk assessment (e.g., hallucinations, lack of understanding)
  • Ethical aspects
  • Role of standards
  • Legal aspects and compliance tips

Session 4: Exploring use cases and future perspectives of AI in finance

  • Real-world applications: fraud detection, portfolio management and customer engagement
  • Fine-tuning AI models for financial tasks
  • Future trends in AI and generative technologies
  • Strategic considerations for AI adoption in financial services

This course aims to provide participants with a comprehensive understanding of how generative AI (GenAI) and large language models (LLMs) are transforming financial services. 

It focuses on equipping learners with the skills to design effective prompts, customise AI models for financial tasks and navigate the ethical and regulatory considerations associated with AI adoption. 

By the end of the course, participants will be able to leverage AI technologies to drive innovation, operational efficiency, and compliance within their organisations.

Who is this course for?

This introductory course might be useful for: 

  • Finance professionals and individuals working in banking, investment, risk management or financial advisory roles who want to understand and leverage AI technologies to enhance their work
  • Decision-makers and leaders such as executives, managers and strategists in financial organisations aiming to integrate AI into their operations effectively

  • Professionals and students who are interested in exploring the intersection of AI and financial services, including its applications, challenges and transformative potential.

Certification

In order to be eligible for a certificate of attendance, you will need to attend the whole course. Participants who meet this criteria will be emailed after the end of the course with a link, and instructions on how to access their University of Oxford digital certificate.

The certificate will show your name, the course title and the dates of the course you attended. You will be able to download your certificate, as well as share it on social media if you choose to do so.

Fees

Description Costs
Course Fee £535.00

Payment

Fees include electronic copies of course materials.

All courses are VAT exempt.

Register immediately online 

Click the 'Book now' button on this webpage. Payment by credit or debit card is required.

Request an invoice

If you require an invoice for your company or organisation, please email us to request an online enrolment form. Payment is then accepted online, by credit/debit card, or by bank transfer.

Application

If you would like to discuss your application or any part of the application process before applying, please click the 'Ask a question' button at the top of this page.

IT requirements

This course is delivered online using Microsoft Teams. You will be required to follow and implement the instructions we send you to fully access Microsoft Teams on the University of Oxford's secure IT network.

To participate you must be familiar with using a computer for purposes such as sending email and searching the Internet. You will also need regular access to the Internet and a computer meeting our recommended minimum computer specification.

It is advised to use headphones with working speakers and microphone.

Terms & conditions for applicants and students

Information on financial support