Imagen de fondo
Finance

Large Language Models in Finance

Applying Large Language Models to Financial Analysis: Hands-on Training and Ethical Insights

clock_icon
17.5h (5 days)
price_icon_white
€800 - €1,400
people_icon_white
Face to Face
language_icon
English
Program date: July 7 - July 11
Early bird deadline: April 15, 2025
Info icon
Learn more
Large Language Models in Finance
Applications for 2025 Summer School programs are now open!
Cta icon Apply

This course focuses on using Large Language Models (LLMs) in Finance, highlighting practical applications. Participants will learn how LLMs work and their limitations, engaging in two hands-on sessions to develop a financial application leveraging LLMs.

Teaching Faculty

Gain hands-on experience using key data science languages to execute advanced financial applications

This course is designed for:

  • Professionals in finance, data science, and management, interested in learning how to use LLMs in their work.
  • Professionals in finance, data science, and management keen to incorporate LLMs into their work.

Participants will explore the details on how LLMs work, their potential and limitations

Participants of this course will:

  • Understand key concepts of Natural Language Processing (NLP) and its applications in finance.
  • Gain foundational knowledge of large language models, including the Transformer architecture and tools like Hugging Face Transformers for financial applications.
  • Develop an understanding of data preparation, training, and fine-tuning techniques for large language models.
  • Explore transfer learning and how pre-trained language models can be customized for specific financial tasks like forecasting and sentiment analysis.
  • Learn how to leverage large language models for business valuation tasks, including forecasting cashflows and conducting scenario analysis.
  • Gain hands-on experience with entity recognition from financial statements and how LLMs can be used for comparable selection in valuations.
  • Master the techniques of fine-tuning large language models for credit risk assessment and estimating probabilities of default.
  • Learn how to deploy LLM applications using a REST API to handle real-world financial decision-making under uncertainty.
  • Explore advanced applications of LLMs in finance, including forecasting returns, fraud detection, and dynamic web scraping of financial data.
  • Understand the ethical considerations and biases in financial models, and how to mitigate them for responsible AI use in finance.

Program Syllabus for Large Language Models for Finance

Here is a list of topics and themes that will be covered during the course:

Introduction to Large Language Models

Plus iconPlus icon
  • Overview of Natural Language Processing (NLP) and its applications in Finance.
  • Introduction to Large Language Models.
  • Understanding the Transformer Architecture.
  • Setting up the Python environment for the course.
  • Introduction to the Hugging Face Transformers Library.

Advanced Topics on Large Language Models

Plus iconPlus icon
  • Preparing and preprocessing data.
  • Training LLMs.
  • Transfer learning and fine-tuning concepts.
  • Pre-trained language models for Finance tasks.

Practical Session I: LLMs for Business Valuation

Plus iconPlus icon
  • Forecasting cashflows using LLMs.
  • Scenario Analysis.
  • Comparable selection using LLMs.
  • Entity Recognition from Financial Statements.

Practical Session II: Credit Risk

Plus iconPlus icon
  • Fine-tuning a model to assess credit risk.
  • Using LLMs to approach complex household decisions under uncertainty.
  • Using LLMs to estimate probabilities of default.
  • Deployment of an application using a REST API.

Other Applications in Finance and Future Trends

Plus iconPlus icon
  • Forecasting Returns.
  • Fraud Detection.
  • Dynamic web scraping of financial information.
  • Ethical considerations and Bias mitigation.

List of References

The course slides and code will be distributed with the course pack. Some additional references are:

Books

Plus iconPlus icon
  • ‘Natural Language Processing with Transformers, Revised Edition’ by Lewis Tunstall, Leandro von Werra, Thomas Wolf, Released: May 2022, Publisher: O’Reilly Media, ISBN: 9781098136796.
  • The Predictive Edge, Alejandro Lopez-Lira, Released: 2024 Publisher: Wiley ISBN: 9781394242719.
  • Quick Start Guide to Large Language Models, Sinan Ozdemir, Released: 2024, Publisher: Pearson Addison-Wesley, ISBN: 9780138199197.
  • Text as Data, Justin Grimmer, Margaret E. Roberts, and Brandon M. Stewart. Released: 2022, Publisher: Princeton University Press, ISBN: 9780691207551.

Why join our Summer School?

All BSE Summer courses are taught to the same high standard as our Master’s programs. Join us to:

1

Network with like-minded peers.

2

Study in vibrant Barcelona.

3

Learn from world-renowned faculty.

Admissions and requirements

It is the participant’s responsibility to ensure they meet the Admissions Criteria.

Program date: July 7 - July 11
Early bird deadline: April 15, 2025

Requirements

Summer School applicants normally demonstrate one or more of the following:

  • A strong background in Economics or a field closely related to the course topic (Statistics, Law, etc.).
  • Postgraduate degree or current Master’s/PhD studies related to the course topic.
  • Relevant professional experience.

Requirements for Large Language Models for Finance

  • Participants should have a basic understanding of Python and finance to engage with LLM applications in the course.
  • No specific readings are required, but participants should familiarize themselves with foundational texts like *Natural Language Processing with Transformers* by Lewis Tunstall et al. and *The Predictive Edge* by Alejandro Lopez-Lira, which are course references.
Apply now

Schedule

Here is your schedule for this edition of BSE Data Science for Finance Summer School, Large Language Models for Finance course.

Time
7
mon
8
tue
9
wed
10
thu
11
fri
11:30 - 13:30
Lecture
16:15 - 17:45
Practical

Credit transfers (ECTS)

To be eligible for credit transfer, students must complete a final project. Students will deliver a short final project one week after the summer school finishes. It will consist in solving a final problem that will include the practical and empirical issues worked on in class.

Please consult the Summer School Admissions page for more information about this option.

Certificate of Attendance

Participants not interested in credit transfer will instead receive a Certificate of Attendance free of charge. These Participants will not be graded or assessed during the course.

Fees for 2025

Multiple course discounts are available, see more information about available discounts. Fees for courses in other Summer School programs may vary.

Course
Data Science for Empirical Finance
Large Language Models in Finance
Modality
Face to Face
Face to Face
Total Hours
17.5
17.5
ECTS
1
1
Regular Fee
1,400€
1,400€
Reduced Fee*
800€
800€

FAQ’s

Need more information? Check out our most commonly asked questions or contact our Admissions Team.

Is accommodation included in the course fee?

Plus iconMinus icon

Unfortunately, accommodation is not included in the course fee. Participants are responsible for finding accommodation.

Are the sessions recorded?

Plus iconMinus icon

Sessions will be recorded and videos will be available for a month once the course has finished.

How much does each Summer School course cost?

Plus iconMinus icon

Fees for each course may vary. Please consult each course page for accurate information.

Are there any discounts available?

Plus iconMinus icon

Yes, BSE offers a variety of discounts on its Summer School courses. See more information about available discounts or request a personalized discount quote by email.

Can I take more than one course?

Plus iconMinus icon

Yes! you can combine any of the Summer School courses (schedule permitting). See the full course calendar.

Cancelation and Refund Policy

Plus iconMinus icon

Please consult BSE Summer School policies for more information

Are there any evening activities during the course?

Plus iconMinus icon

A social dinner will take place during the week for all participants, it is free to attend.

Contact our Admissions Team

Related Courses

Summer School
Menu
Finance

Advanced Portfolio Management

Calendar Icon
June 30 - July 4
Subscribe to our newsletter
Want to receive the latest news and updates from the BSE? Share your details below.
Founding institutions
Distinctions
Logo BSE
© Barcelona Graduate School of
Economics. All rights reserved.
YoutubeFacebookLinkedinInstagramX