Financial engineering draws on tools from
applied mathematics,
computer science,
statistics and
economic theory. In the broadest sense, anyone who uses technical tools in finance could be called a financial engineer, for example any
computer programmer in a
bank or any
statistician in a government economic bureau. However, most practitioners restrict the term to someone educated in the full range of tools of modern finance and whose work is informed by financial theory. It is sometimes restricted even further, to cover only those originating new financial products and strategies. Despite its name, financial engineering does not belong to any of the
fields in traditional professional engineering even though many financial engineers have studied engineering beforehand and many universities offering a postgraduate degree in this field require applicants to have a background in engineering as well. In the United States, the
Accreditation Board for Engineering and Technology (ABET) does not accredit financial engineering degrees. In the United States, financial engineering programs are accredited by the
International Association of Quantitative Finance.
Quantitative analyst ("Quant") is a broad term that covers any person who uses math for practical purposes, including financial engineers. Quant is often taken to mean "financial quant", in which case it is similar to financial engineer. The difference is that it is possible to be a theoretical quant, or a quant in only one specialized niche in finance, while "financial engineer" usually implies a practitioner with broad expertise. "
Rocket scientist" (
aerospace engineer) is an older term, first coined in the development of rockets in WWII (
Wernher von Braun), and later, the
NASA space program; it was adapted by the first generation of financial quants who arrived on
Wall Street in the late 1970s and early 1980s. While basically synonymous with financial engineer, it implies adventurousness and fondness for
disruptive innovation. Financial "rocket scientists" were usually trained in applied mathematics,
statistics or finance and spent their entire careers in risk-taking. They were not hired for their mathematical talents, they either worked for themselves or applied mathematical techniques to traditional financial jobs. ==Criticisms==