Financial engineering is an interdisciplinary field that combines applied mathematics, statistics, and computer science to guide investment decisions. While finance has always emphasized quantitative analysis, today’s technology has made it possible to apply these approaches at an unprecedented scale and speed. Massive datasets are now delivered via hardwired internet connections into financial modeling programs built in software like Solver in Microsoft Excel, or even machine learning tools created through Python programming or other techniques.

The power of financial engineering has made it incredibly important for trading, portfolio optimization and risk management, valuation of derivatives and real options, and a host of other purposes at virtually all of today’s largest financial institutions. Indeed, it has been estimated that as much as 80% of the activity on the U.S. stock market today is computer-led algorithmic trading, making the use of financial engineering absolutely essential to competitiveness in the market.

By automating financial decision-making, these approaches have unquestionably created enormous value for the firms deploying them. However, the prominence of financial engineering has caused some economists to question whether it is contributing to market volatility during financial turbulence, including the COVID-19 crisis, even if many others claim that it has a positive effect on market liquidity. Regardless, financial engineering is here to stay, making it a critical topic to understand for any finance professional.‎

Today, any career in finance requires at least a familiarity with financial engineering. Whether you go to work at an investment bank, a hedge fund, an insurance company, or in government treasuries or regulatory agencies, these techniques will continue to shape the landscape of your job. Thus, understanding how to use financial engineering approaches and how they impact financial problems is a valuable asset regardless of your role in this industry.

If you have a particular talent for applied mathematics and computer science, you can pursue a lucrative career in financial engineering yourself, as quantitative analysts or “quants” are some of the most highly sought after professionals in the industry. “Back office” quants generally build and validate complex financial engineering tools, while “front office” quants work directly with traders to help them deploy the pricing and trading tools they need.‎

Absolutely. Coursera offers a wide range of courses in financial engineering as well as related areas of this interdisciplinary field, including business, computer science, and mathematics and statistics. These courses as well as multi-course Specializations are offered by some of the top undergraduate and business schools in the country, including Columbia University, Yale University, and the University of Pennsylvania.

In addition to being able to learn remotely on your own schedule, these courses are also available at a significantly lower tuition than their on-campus counterparts. Thus, you won’t need a spreadsheet to determine that learning about financial engineering online is a smart investment in your future, whether you’re just starting your career or are an experienced finance professional looking to update your understanding of this vital topic.‎