Business Schools Are Launching Even More FinTech, Big Data & Blockchain Courses

From Oxford to NYU Stern, business school has become the go-to place for courses on financial technology

The financial services sector is scrambling to harness the power of financial technology—fintech—so as to improve efficiency, generate new products and services, and avoid being disrupted by nimbler startups.

As they race to embrace technology from blockchain and cryptocurrencies to artificial intelligence and machine learning, they need employees with business smarts and who are also digitally-savvy. However, finding people with both skillsets is hard.

Business schools are trying to plug that gap with a slew of new courses to help students and financial services professionals understand how to apply fintech to finance and shape the future of banking.

Imperial College Business School in London has just launched an MSc in Fintech. It expects 60 computer-literate students to begin classes in September next year, paying £34,500 ($44,000) for the one-year course and learning about finance theory, data science, and fintech innovation.

James Sefton, economics professor and...

he MSc, says: “Our feedback from the industry, which is certainly in line with our experience, is that these students are not easy to find.”

Research by Innovate Finance and WPI Economics found that 30,000 new jobs will be created in the UK over the next decade because of fintech, and it is also altering many of the more traditional banking roles. For example, JPMorgan recently made coding lessons mandatory for all of its new investment bankers and money managers.

Imperial, a STEM-focused university, hopes to combine its business school with engineering and computer science departments to teach the Fintech Msc. It also plans to leverage its close links to the large financial services firms on its doorstep in the City, plus the fintech startups in London, such as Transferwise or Monzo.

“We expect our graduates to work in tech-driven roles in finance, including big data, financial research, algorithmic trading, transactions, and peer to peer lending,” says James.

“They may work in the fintech industry, including challenger banks and startups, or they may work for more established banks, hedge funds and consulting firms.”

Kathleen DeRose, clinical associate professor of finance at NYU Stern School of Business in the US, says: “Fintech is one of the fastest growing segments of the economy, and students will need an understanding of data science to be prepared for the future of work.”

Stern was among the first to teach fintech, offering a bitcoin course back in 2014, and it established a fintech MBA specialization in 2016. In the 2018/19 academic year, the school plans to offer 12 distinct graduate fintech courses including on robotic wealth advisers, fintech analytics and cryptocurrency investing.

“Finance is changing more quickly today than at any time since the Renaissance, when modern accounting first came into wide use,” says David Yermack, finance chair at Stern.

“We are now seeing markets being recreated by machine learning, artificial intelligence, and decentralized consensus systems. It is an exciting and very interesting time.”

Increased market interest in AI prompted the University of Oxford’s Saïd Business School to create an algorithmic trading course this year. Hundreds of students have already taken the six-week program, which teaches them about successful trading strategies using computer algorithms, how to build them and what lessons more traditional financiers can learn from them.

Some students have already developed algos and have put them to work in real markets over the past few months.

Algorithmic trading is increasingly popular with hedge funds, and about 20% of the industry now uses such strategies, according to Oxford. Commonly known as 'quant' funds, these investors use computers to spot changes or patterns across markets and make trading decisions based on the data.

Nir Vulkan, associate professor of business economics and convenor of the Oxford Algorithmic Trading Program, says the method removes emotion from trading decisions. “The idea is that good traders follow good rules, and removing the human completely means you are better able to follow these good rules, and not be affected by emptions,” he says.

“Also, algos can trade many markets at the same time, carrying out complicated computations that humans would struggle with. And similarly, algos can manage very quick decisions, what we call high frequency trading, which humans could not obviously do.”

Oxford has recruited some big names from the largest algo funds around to teach the course, such as Matthew Sargaison, joint CEO of Man-AHL, and Martin Luek, founder of Aspect Capital.

It is not just western business schools helping financiers master technology. CUHK Business School in Hong Kong offers a finance and technology concentration as part of its MBA degree, in which students learn how to manage innovation, technology, and apply AI and machine learning to finance.

In addition, the Chinese school last year launched an MSc in Management designed to prepare millennials for the fast-changing business environment, with courses covering fintech, big data and digital innovation.

Elsewhere, Frankfurt School of Finance & Management in Germany runs a data analytics and machine learning module as part of its masters in finance degree.