Steve Yang Ph.D., financial engineering professor at the School of Systems and Enterprises (SSE) at Stevens Institute of Technology, has been nominated to the Distinguished Visiting Scholars Program at the Securities and Exchange Commission (SEC). The highly-selective scholars program invites academic researchers from leading universities. During his week-long visit, Yang will collaborate with SEC economists and staff, and provide expert insights on matters of great importance to the SEC.
Dr. Yang’s research, which intersects XBRL technology, text analytics and finance, was recognized by the Division of Economic and Risk Analysis (DERA), the arm of the SEC charged with integrating financial economics and data analytics into the agency’s central mission.
“I’ve been doing research related to using XBRL technology and text analytics to extract information automatically from structured and unstructured data in disclosures,” Yang said. “These types of technologies can help regulators identify misleading information in disclosures.”
Identifying anomalies in corporate financials
Thousands of financial filings are reviewed by a handful of examiners at the SEC each quarter. They are tasked with closely reading the financial disclosures of companies with two goals in mind: to make sure that the information disclosed by corporations is accurate and to protect investors from falsified information. If the SEC examiners find problems, they engage the companies and begin a dialogue.
“In the past, forms of manipulation in financial disclosures were done through phone calls and emails,” said Yang. “However, now with the Internet, smart phones and social media – all the platforms used today – people have at their disposal all different types of media to manipulate the market.”
As newer technologies transform the way companies publicize and share financial disclosure information, regulators are increasingly challenged in verifying the accuracy of the data and detecting fraud. Yang’s research in text analytics and algorithmic trading can help regulators identify outliers in corporate financials.
“There are algorithms out there that can read content like news articles and text disclosures,” said Yang. “By using these algorithms, regulators can detect certain patterns that will be useful for different purposes such as fraud identification and enforcement.”
As for his nomination to the scholars program, Yang said, “I’m really honored to be chosen as a scholar and look forward to the exchange of ideas.” He adds that other SSE faculty can offer expertise in various areas useful to the SEC, particularly in regards to financial information text mining.
“An ongoing collaborative relationship between the SEC and SSE will not only help to uncover opportunities for innovation in financial regulation, but also strengthen our academic research efforts,” said Yang.