Fintech, AI and sustainable finance - Curriculum - Cambridge Judge Business School (2024)

Finance technology and artificial intelligence

Fintech, AI and sustainable finance - Curriculum - Cambridge Judge Business School (1)

In a rapidly evolving finance landscape, we are committed to staying at the forefront of financial education.

We have introduced and developed cutting-edge technical courses and recruited specialist practitioners to prepare you for the applications of new and emerging technologies across the financial services industry.

Students will cover the foundational concepts of machine learning, looking at concrete applications in trading, asset management, accounting and auditing, marketing and operations. Hands-on machine learning and applied machine learning for finance practitioners will provide you with an in-depth grasp and understanding of the main tools and concepts of AI and machine learning.

You will become part of our AI and Machine Learning community and will have access to free online tutorials, podcasts, advice, and community support.

Elective courses

Elective courses in this area include:

This course aims to provide students with an overview of quantitative techniques that are relevant to strategic asset allocation, whereby allocations are long-term, multi-asset, and institutional in nature.
The module is organised by areas of asset management, and each case will be accompanied by related quantitative techniques including financial, mathematical, and statistical basics.

The course provides a unique opportunity to understand how the theory of Finance, Statistics and Econometrics can be applied to making concrete and scientifically based investment decisions in the financial markets. The course will build a practical bridge between abstract concepts and everyday practice.

This course will provide a foundational knowledge of the blockchain technology and go over a number of its key applications, providing students with a solid understanding of what blockchain is, how it works, and how it can be applied in the financial services industry and beyond.

This course offers a comprehensive tour from Mathematical Foundations to their computational implementation and finally the business application. The purpose of the course is to introduce students to the Mathematical and Computational ideas and tools behind Fintech to better understand the potential and limitations of these new tools to a point where students can understand the opportunities and challenges of innovation in this field.

Sustainable finance and ESG

Fintech, AI and sustainable finance - Curriculum - Cambridge Judge Business School (2)

Cambridge University is uniquely positioned in the area of sustainability, with a large set of academics, departments and research centres across the School and University engaged on these topics.

We recognise the growing importance of ESG factors in the finance industry, so we have introduced and developed a range of topical courses focussed on sustainable finance and ESG related topics.

You will have several opportunities to not only learn about sustainability and apply your learning to real-life situations, through core courses, elective courses and project work, but to also learn from our experienced finance faculty and expert guest speakers from a variety of industries. For students who are interested in these topics, there are also opportunities to work with research centres such as The Circular Economy Centre and The Cambridge Institute for Sustainability Leadership.

Elective courses

Elective courses in this area include:

In this course students will learn about the difference between a traditional economic model and circular economic model and how to establish the business and financial case for adopting a circular economy model at all levels in the economy.

This course begins with a question; what is the purpose of the finance industry? Unless we answer that question, it is unlikely we will build a purposeful industry to which professionals might wish to devote their careers.

If we do, we discover that finance is essential for the effective operations of the economy. But we also discover that, as currently constituted, the evidence suggests it is inefficient. The course investigates why this might be.

The aim of this course is to describe, understand and discuss current developments and trends in the area of sustainable finance, with a special focus on climate risk and ESG.

With the help of expert guest speakers, we shall look to distinguish between different types of sustainable finance products and relevant eligibility criteria. The course looks at how various ESG scoring and assessment approaches have been applied to real life case studies. It also explores how sustainable finance is evolving in emerging markets, with a special focus on Latin America.

Faculty and practitioners who specialise in these fields

Andrei Kirilenko

Professor of Finance

Professor of Finance

Director of the Doctoral Programme

Founding Director of the Cambridge Centre for Finance, Technology & Regulation (CCFTR)

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Khaled Soufani

Management Practice Professor of Financial Economics & Policy

Management Practice Professor of Financial Economics & Policy

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Director of the Cambridge Executive MBA Programme

Director of the Circular Economy Centre (CEC)

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Oğuzhan Karakaş

Associate Professor in Finance

Associate Professor in Finance

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Director of the MPhil in Finance Programme

Co-Director of the Centre for Endowment Asset Management (CEAM)

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Fintech, AI and sustainable finance - Curriculum - Cambridge Judge Business School (7)

David Pitt-Watson
David Pitt-Watson

Fellow (Finance)

Fellow (Finance)

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David holds an honorary title from Cambridge Judge Business School.

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External lecturers

Fintech, AI and sustainable finance - Curriculum - Cambridge Judge Business School (8)

Dr Alejandro Reynoso

Dr Alejandro Reynoso teaches the Machine Learning for Finance Practitioners programme on the MFin.

He holds a PhD in Economics from MIT and his career combines teaching, research, and practice. He has spent the last 25 years leading institutional change and financial innovation in Latin America.

His academic activity emphasises the creation of interactive materials for training financial professionals in the use of mathematics and computational methods in the areas of machine learning, decentralised finance, algorithmic trading, and investment banking.

He is a founding partner and Chairman of the Board of one of the first Blockchain-Investment-Banking advisory firms in Latin America, based in Peru, participating in projects encompassing real estate, reforestation, and professional sports.

Previously, he was the project leader of initiatives such as the Reform of the Pension System in Mexico, the creation of the Systemic Risk Management Unit at the Mexican Central Bank, the corporate reorganisation and IPO of the Mexican Stock Exchange, the implementation of the first ETFs in Colombia, Mexico and Peru in the Long-only, Inverse and Leveraged and Fixed Income segments; he led the establishment of the REIT Industry in Mexico.

He has worked in high-level executive positions for the Ministry of Finance of Mexico and the Mexican Central Bank, the Mexican Stock Exchange, Barclays Global Investors, Evercore Partners, and Grupo Televisa.

He founded and listed the first real estate internally managed REIT in Mexico, where he was a General Partner and Chairman of the Control Group. In 2021, this company merged with Skyway Equities, one of the largest real estate developers and operators in Latin America, where he now co-heads its Investment Banking Unit.

He has been awarded twice the Banamex National Prize of Economic Research in Mexico. He was a Visiting Scholar at the National Bureau of Economic Research in 2001, and since 2014 he has taught the following courses at Cambridge Judge Business School, University of Cambridge:

  • Algorithmic Trading
  • Mathematical Foundations of Fintech
  • Machine Learning for Financial Practitioners
  • Financial Innovation in Emerging Markets.

He has also taught at ITAM in Mexico for 16 years.

Research centres and initiatives

With a research focus on circular economy, circular business models and their application, as well as the policy and business contexts within which they operate, the Centre combines academic rigour alongside practitioner engagement, in line with the research strategy of Cambridge Judge Business School.

An impact-led institute within the University of Cambridge that activates leadership globally to transform economies for people, nature and climate.

The Cambridge Centre for Finance, Technology & Regulation serves as a hub for research, education and outreach on the impact of digital technologies on the financial services industry.

The Cambridge Centre for Alternative Finance studies alternative finance, including financial channels and instruments that emerge outside of the traditional financial system.

A unique partnership between 8 leading European business schools that helps present and future leaders combat the climate crisis facing the planet.

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Fintech, AI and sustainable finance - Curriculum - Cambridge Judge Business School (9)

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Staying on trend: AI, big data and blockchain on the Master of Finance

As AI, big data, blockchain and other areas continue to grow apace, how is the Cambridge Master of Finance keeping up? We spoke to 2 MFin alumni to find out how the programme helped in these areas, and what impact it’s had on their careers.

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Fintech, AI and sustainable finance - Curriculum - Cambridge Judge Business School (10)

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Programme news

Considering a career in ESG? How the MFin can help get you there

With ESG and sustainability taking on an increasingly important role in the finance industry, more and more opportunities are opening up in Sustainable Finance and beyond – so what’s it like to work in the field, and how can the MFin help prepare you for a career in it? We spoke to 2 alumni from the Cambridge MFin to find out.

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I'm deeply entrenched in the intersection of finance, technology, and artificial intelligence (AI), with a profound understanding of how these domains converge to shape the modern financial landscape. My expertise spans various facets, including machine learning applications in trading, asset management, accounting, auditing, marketing, and operations within the financial services industry.

In the realm of finance technology, I'm well-versed in cutting-edge technical courses designed to equip individuals with the skills needed to navigate the evolving financial ecosystem. These courses delve into foundational machine learning concepts, providing hands-on experience and practical knowledge essential for finance practitioners. Moreover, I'm familiar with the intricacies of blockchain technology and its applications in revolutionizing financial services, offering insights into its workings and potential impacts.

Now, let's dissect the concepts mentioned in the provided article:

  1. Quantitative Techniques for Asset Allocation: This elective course focuses on strategic asset allocation, integrating long-term, multi-asset perspectives with institutional considerations. It encompasses various quantitative techniques, including financial, mathematical, and statistical basics, to facilitate scientifically informed investment decisions in financial markets.

  2. Blockchain Technology: Another elective course introduces students to blockchain technology, elucidating its fundamental principles, functionalities, and applications across the financial services industry and beyond. It aims to provide a comprehensive understanding of blockchain's potential and its implications for financial innovation.

  3. Mathematical and Computational Foundations of Fintech: This course offers a comprehensive exploration of mathematical and computational concepts underpinning financial technology (Fintech). It bridges theoretical knowledge with practical applications, enabling students to grasp the opportunities and challenges associated with Fintech innovation.

  4. Sustainable Finance and ESG: Cambridge University emphasizes sustainability in finance through specialized courses and research initiatives. These courses delve into topics such as the circular economy, climate risk, and ESG (Environmental, Social, and Governance) factors' integration into financial decision-making. They aim to equip students with the knowledge and skills to navigate the evolving landscape of sustainable finance.

The faculty members mentioned in the article, including Andrei Kirilenko, Khaled Soufani, Oğuzhan Karakaş, and David Pitt-Watson, contribute significantly to research and education in finance, technology, and sustainability at Cambridge University. Additionally, external lecturers like Dr. Alejandro Reynoso bring practical insights and industry experience to enhance learning experiences for students.

Furthermore, research centers and initiatives such as the Cambridge Centre for Finance, Technology & Regulation and the Circular Economy Centre demonstrate Cambridge University's commitment to advancing interdisciplinary research and addressing contemporary challenges in finance and sustainability.

In summary, the article highlights Cambridge University's efforts to integrate finance, technology, and sustainability through innovative educational programs, expert faculty, and collaborative research endeavors, reflecting the institution's leadership in shaping the future of finance.

Fintech, AI and sustainable finance - Curriculum - Cambridge Judge Business School (2024)


How long is the Mfin program at Cambridge University? ›

The Master of Finance programme starts in mid-September each year and runs for 12 months.

Is a master in fintech worth it? ›

Fintech is a fast-growing area that provides lucrative career options. Combining financial knowledge with quantitative skills, based on analytical fundamentals and artificial intelligence will give you an edge in your career growth.

What is the fintech innovation course? ›

Course Delivery

This programme is delivered online part-time over four semesters i.e. from September 2024 to June 2025 and from September 2025 to May 2026. The capstone project is completed in the student's own time during the period of May to August 2026.

What is a master's in finance degree? ›

The Artificial Intelligence master's degree program is designed as a 30-credit hour curriculum that give students a comprehensive framework for artificial intelligence with one of 4 concentration areas: (1) Computer Vision, (2) Intelligent Interaction, (3) Machine Learning, and (4) Knowledge Management and Reasoning.

What is the acceptance rate for Cambridge Judge MFin? ›

Eligibility Entry Requirement
Acceptance Rate25.4%
Application FeeGBP 120 (INR 12459)
Decision TimeWithin three weeks of the relevant deadline
InterviewOffline or via Zoom video
4 more rows

What is the acceptance rate for Cambridge finance? ›

Cambridge University acceptance rate stands around 20-21%. All the Cambridge University courses have entry requirements requirements for admissions. Key admission requirements are listed below: Professional Bachelor's (at least 4 years) in professional subjects from a Well-Ranked Institution with a CGPA 7.3+.

What is the highest salary in fintech? ›

Highest salary that a Product Manager can earn in FinTech companies is ₹40.0 Lakhs per year (₹3.3L per month).

Is fintech a high paying job? ›

As of Apr 6, 2024, the average annual pay for a Fintech in the United States is $123,495 a year. Just in case you need a simple salary calculator, that works out to be approximately $59.37 an hour.

Is fintech a hard major? ›

Learning FinTech involves mastering industry-specific tools such as Python, as well as constantly staying ahead of technological innovation in the field. Professionals in FinTech need to combine both hard skills, such as data visualization and programming, with soft skills like communication and business acumen.

Which FinTech course is best? ›

Which are the best FinTech Courses available in the market?
  • Certified Blockchain Expert by Blockchain Council.
  • Udacity's Digital Transformation for Financial Services.
  • Introduction to FinTech: edX.
Feb 8, 2024

Is FinTech in high demand? ›

Financial and Monetary Systems

The global financial technology (fintech) industry is booming, with customer demand driving growth.

What should I study to get into FinTech? ›

Data analytics, Artificial Intelligence, and Python Programming are critical areas to study before embarking on a career in FinTech.

Which AI degree is best? ›

A computer science degree is a common choice since AI is a subdiscipline of computer science. But a data science degree, which also comes with AI skills, may be equally useful because it's one of the most in-demand.

Is Masters in AI difficult? ›

Cons of Master's in AI Degrees

These degree programs are challenging. While this prepares you for real-world problems you will face in your career, you need to make sure you are ready for them. These programs are not suited for students that are not passionate about artificial intelligence.

Is it better to have an MBA or a masters in finance? ›

The MBA equips graduates with a broader skill set and knowledge base composed of multiple aspects of the business world. An MF program, on the other hand, is much more finance specific. The applicant's career goals will largely determine which type of program they choose.

How long is the M Eng program? ›

Typical completion time for full-time Master of Engineering students is 12-16 months.

How many years is the Cambridge MBA program? ›

A one-year MBA degree from Cambridge Judge Business School, at the heart of the University of Cambridge.

How long is the Masters program at Cambridge? ›

MSts are academically rigorous postgraduate programmes, containing a significant taught element and a research project and associated dissertation, usually undertaken over two years.

How many years is Cambridge architecture program? ›

Becoming an architect

You can do this by studying at Cambridge: A full-time, 2-year Master of Architecture (MArch) course, plus a one-year, part-time Postgraduate Certificate in Professional Practice. A part-time, 4-year MSt Apprenticeship, during which you will work.


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