MSC FINANCIAL ENGINEERING

The Complete Guide: Financial Engineering vs. Financial Technology

The financial industry is experiencing enormous changes as a result of mathematics. Advances in computing technology and low-cost cloud storage services have allowed individuals to build sophisticated investment strategies from the comfort of their homes. On a larger scale, banks, software companies, and even governments are refining the mathematical models used in financial markets to create more robust policies and valuable strategies.

It’s an exciting time to enter the world of finance, particularly as technology continues to transform the industry. However, in the face of such rapid changes, one question inevitably arises: how can one break into the field and stay relevant?

Financial Engineering vs Financial Technology

Dr. Charlie Charoenwong is an associate professor at the Nanyang Business School (NBS), Nanyang Technological University Singapore (NTU), and is among the experts who believe the world is becoming increasingly quantified and numerical. He asserts, “Take a look around you. Mathematics is ubiquitous.”

Indeed, advanced mathematics has revolutionised the world in just a few years. Recently, ChatGPT, an artificial intelligence (AI) based on deep learning that understands and generate human-like responses to text-based queries has propelled to meteoric success across all professional groups. At Changi Airport, facial recognition tools based on mathematical principles streamline security and immigration processes. And through mathematics online shopping deliveries arrive at consumers’ doorsteps in days, if not hours, regardless of the season.

The financial industry is also experiencing enormous changes as a result of mathematics. Advances in computing technology and low-cost cloud storage services have allowed individuals to build sophisticated investment strategies from the comfort of their homes. On a larger scale, banks, software companies, and even governments are refining the mathematical models used in financial markets to create more robust policies and valuable strategies.

It’s an exciting time to enter the world of finance, particularly as technology continues to transform the industry. However, in the face of such rapid changes, one question inevitably arises: how can one break into the field and stay relevant?

Engineering, Finance, Technology, and Everything in between

Many students today face a dilemma when deciding which skills to pursue at the intersection of finance and technology. They are unsure which programming language to learn first, whether an IT degree is still relevant, or the differences between data analysis, financial engineering, and fintech.

According to Dr. Charlie, “broad fintech” roles, such as those in contactless credit cards, eWallets, and money transfer apps, do not necessarily require advanced mathematics. While entrepreneurs in fintech startups may come from diverse industries, such as marketing or human resources, what they need is a “good” idea. As for code writing, AI can do most of it, if not all.

In contrast, financial engineering demands a strong understanding of math, programming, and finance theory. Pricing complex financial products or designing risk models in banking or investments require data interpretation and applying a rich knowledge of capital markets, statistics, and stochastic calculus to develop executable programs.

“Despite the huge amount of financial data available, Dr. Charlie notes that the future of markets remains uncertain. Mathematical models and statistical analysis can help financial engineers extract market opinions about the future and take advantage of pricing discrepancies in financial markets.”

The curriculum of the Specialised Master’s Degree in Financial Engineering (MFE) at the NBS prepares graduates to use tools to solve real-world financial problems, leveraging finance theory and experience to manage risk and optimise investment portfolios.

What does a future in financial engineering look like?

NBS launched the MFE programme in 1999, with technical support from the Tepper School of Business and the Department of Mathematical Sciences at Carnegie Mellon University. Dr. Charlie, who played a key role in designing and managing the programme, notes that even before the MFE was introduced, there was already a growing emphasis on mathematics and computing worldwide.

In more than two decades since its inception, mathematical skills have contributed to various advancements, such as developing life-saving vaccines, constructing artificial islands, and cultural exchange between nations. Many global leaders, including Elon Musk and Xi Jinping, also hold engineering degrees. Dr. Charlie explains that the quantitative and analytical skills taught in the MFE programme will remain relevant, even for graduates who transition to other industries or become top executives in the future.

NBS MFE programme’s emphasis on teamwork and communication, current financial theory and computational methods, and holistic thinking have consistently produced graduating classes that secure full-time employment or internships within three months of graduation. These skill sets apply to anyone seeking a strong foothold in the financial services industry.

Accounting and Auditing
We had students who joined the MFE programme with accounting degrees, and upon completing the study, they may choose to return to roles in auditing and accounting. Large corporations often have extensive portfolios with various financial products and assets. To manage the fluctuations in the value of these products, businesses need a reliable risk model that can estimate the required capital to support them.

According to Dr Charlie, “A guarantee or MOU can be a potential financial liability even if no product has changed hands. Many similar products may not be recorded in the traditional financial system.” A financial engineer can utilise historical data to estimate the value of various financial products or contracts that a company holds positions on, including informal ones, and prepare accordingly.

Financial Software and Financial Data Provider
Some of our MFE graduates go on to join risk management software companies or financial data providers. Employees at such businesses are often asked to customise financial tools, applications, and terminals to solve client-specific problems.

Quant Trading
Quantitative trading firms use historical data to generate buying and selling signals. Successful quant traders must have strong foundational programming skills, a solid understanding of mathematics, and knowledge of financial concepts and issues.

According to Dr Charlie, fixing a programme that has a syntax error is relatively easy and can be done by AI. However, if a programme appears to work but contains conceptual errors, incorrect assumptions, or inaccurate data, the resulting conclusions could lead the company astray. This can result in financial risk or unnecessarily high costs for the company. To avoid such risks, quant traders properly trained in financial engineering is needed for this task.

What lies ahead?
In the modern digital age, everything is recorded in a code-able format. Those with strong mathematical and programming skills are better equipped to make sense of these numbers and spot trends faster than the average person.

The applications of mathematics go beyond just finance. Artistic concepts can also be somewhat quantified, as evidenced by the recent rise of AI-supported art, music, and writing. Despite common assumptions that math and programming are tedious, the MFE programme opens up new career paths prioritising innovation and strategy. Graduates must apply their interdisciplinary knowledge to solve new problems creatively.

With the potential for high earnings and the ability to transfer skills across industries, a Specialised Master’s Degree in Financial Engineering from NBS is a valuable asset for any forward-thinking individual.

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