{"id":33578,"date":"2026-03-20T13:41:36","date_gmt":"2026-03-20T20:41:36","guid":{"rendered":"https:\/\/www.uwb.edu\/news\/?p=33578"},"modified":"2026-03-20T13:46:01","modified_gmt":"2026-03-20T20:46:01","slug":"predicting-insider-trading-with-ai","status":"publish","type":"post","link":"https:\/\/www.uwb.edu\/news\/2026\/03\/20\/predicting-insider-trading-with-ai","title":{"rendered":"Predicting\u00a0insider trading with AI\u00a0"},"content":{"rendered":"\n

The U.S. Securities and Exchange Commission prosecutes about 50 cases of insider trading on average each year. As many scholars and regulators agree, however, these cases\u202flikely represent only a fraction of the illegal insider trading that happens each year. <\/p>\n\n\n\n

According to a study from the University of Technology Sydney, the true number of incidents\u202fcould be at least four times higher. <\/p>\n\n\n\n

Illegal insider trading refers to the buying or selling of financial securities, such as stocks or bonds, using information that is not available to the public. Although insiders\u202fare required to\u202freport their transactions to the SEC, illegal trading is still difficult to catch and even harder to prove. <\/p>\n\n\n\n

In her latest research, Dr. Solmaz Batebi, an assistant teaching professor\u202fin\u202fthe University of Washington\u2019s School of Business<\/a>, looks\u202fto\u202fartificial intelligence as a potential tool for improving insider trading predictions. <\/p>\n\n\n\n

Bridging two languages<\/strong> <\/h2>\n\n\n\n

Growing up in Iran, Batebi was always interested in money and fascinated by her uncle, who worked in the stock market. She saw him as a role model \u2014 a knowledgeable person who everyone trusted. \u201cI wanted to be like him,\u201d she said. <\/p>\n\n\n\n

\"A
Dr. Solmaz Batebi.<\/figcaption><\/figure>\n\n\n\n

\u201cWhat I like about finance,\u201d she added, \u201cis that\u202fit\u2019s\u202fa dynamic world. Everything\u202fthat happens in the world, you see the market reaction,\u202fand you see how people react to the news. You can learn a lot about sociology, psychology,\u202fmath\u202fand more. That\u2019s what I love about it.\u201d <\/p>\n\n\n\n

Batebi worked in market surveillance and regulatory development at the Tehran Stock Exchange, where she helped design and implement data-driven compliance tools and updated regulations addressing market manipulation and high-frequency trading. She became interested in algorithms and data science at play in surveilling the market. <\/p>\n\n\n\n

At the time, it was uncommon for finance experts to also have computer science knowledge and skills, she said. \u201cThe software engineers\u202fdidn\u2019t\u202fhave\u202fthe\u202fbusiness acumen, and we didn\u2019t have the coding\u202fskills. There\u202fwasn\u2019t\u202fa common language between us, so I became interested in bridging those two things.\u201d <\/p>\n\n\n\n

She began teaching herself coding skills and taking computer science courses. Then, she took her studies abroad to the U.S. <\/p>\n\n\n\n

Connecting finance and computer science<\/strong> <\/h2>\n\n\n\n

Batebi received a doctorate in Business Administration with a concentration in Finance from the University of Texas Rio Grande Valley. Under the mentorship of Dr. Ahmed Elnahas, an associate professor at UTRGV, she continued exploring the intersection of finance and computer science. <\/p>\n\n\n\n

She became increasingly interested in how artificial intelligence could be\u202fleveraged\u202fin the market \u2014 particularly for insider trading analysis. Batebi then devoted her dissertation to the topic, and recently published her findings in a paper, \u201cAre machines better predictors of insider trading?<\/a>\u201d <\/p>\n\n\n\n

\u201cWhen you want to prove that someone has done something illegal, you need to be able to prove their intention,\u201d she said. \u201cProving that is\u202freally hard, and often you\u202fdon\u2019t\u202fknow if they saw a gain because they have certain information or because they just know the market well. <\/p>\n\n\n\n

\u201cI wanted to know: How can I answer those questions by using AI?\u201d <\/p>\n\n\n\n

While her mentor knew little about how AI intersected with finance, Batebi said Elnahas eagerly supported her in investigating the topic. After graduation, she had initially planned to\u202fagain work\u202fin the stock market \u2014 but her passion for the research and encouragement\u202ffrom\u202fElnahas inspired her to enter the world of academia. <\/p>\n\n\n\n

Analyzing human decision making<\/strong> <\/h2>\n\n\n\n

Batebi\u2019s research revealed that machine learning methods\u202fsubstantially outperformed traditional methods of predicting both the likelihood and\u202fthe magnitude\u202fof insider sales. Because human decision making is complex, she noted that more linear models often\u202ffail to\u202ftake all the variables into account. AI, for its part, excels at synthesizing and analyzing information and behavior patterns. <\/p>\n\n\n\n

The biggest advantage in using AI,\u202fthough,\u202fwas speed. \u201cBefore AI, investigations on a single trade could take six months to a year to understand the intention,\u201d Batebi said. \u201cWith AI, much of that same workload can happen in a couple minutes.\u201d <\/p>\n\n\n\n

In analyzing trading behaviors, Batebi also found a significant difference across genders. While male traders acted more based on incentive, female traders appeared to rely more heavily on information. <\/p>\n\n\n\n

\u201cMale insiders are more adventurous.\u202fThey\u2019re\u202frisk lovers. Instead of putting trust in the information they use, they are motivated by an incentive for increasing their salary,\u201d she said. \u201cBut women are more risk averse.\u202fThey put their trust in information to make a decision, and they don\u2019t want to act without having enough knowledge.\u202fThey\u2019re\u202fmore conservative in that sense.\u201d <\/p>\n\n\n\n

As a result of that general difference in behavior, Batebi saw more pronounced predictive gains among female insiders. <\/p>\n\n\n\n

“I always tell my students that you need a superpower in the job market.”<\/p>Dr. Solmaz Batebi, assistant teaching professor, School of Business <\/cite><\/blockquote><\/figure>\n\n\n\n

Finding a superpower<\/strong> <\/h2>\n\n\n\n

In\u202ffall\u202f2025, Batebi joined the faculty at UW Bothell, where she now teaches finance. She brings her computer science expertise\u202finto the classroom as well to help students develop analytical and technical skills relevant to both academia and industry \u2014 bridging theory with real-world financial applications. <\/p>\n\n\n\n

\u201cI always tell my students that you need a superpower in the job market,\u201d she said. \u201cJust getting a certificate or a degree is not enough. Having something beyond this, like coding and computer science skills, is a real plus, and it can be a superpower for you.\u201d <\/p>\n\n\n\n

Batebi also welcomes students into her research and\u00a0said she\u00a0is eager to help them on the journey to publishing their own work.\u00a0Her next\u00a0research\u00a0paper\u00a0will\u00a0examine how AI can be applied in investment banking and wealth management.\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"

Dr. Solmaz Batebi\u202fleverages\u202fartificial intelligence to take a closer look at insider trading.\u00a0<\/p>\n","protected":false},"author":121,"featured_media":33579,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_is_archived":false,"_archived_contact_email":"","footnotes":""},"categories":[202,229,214],"tags":[],"school":[417],"class_list":["post-33578","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-campus-news","category-faculty","category-research","school-school-of-business"],"acf":{"related_links":{"toggle_visibility":false,"link_1":"","link_2":"","link_3":"","link_4":"","link_5":""},"highlight_box":{"toggle_visibility":false,"title":"","content":"","button":"","button_style":"angled-purple-button","button_screen_reader_text":""},"contact_type_1":{"toggle_visibility":true,"contact_title":"","email":"","phone":"","box":"","address_line_1":"","address_line_2":"","location":""},"contact_type_2":{"toggle_visibility":false,"contact_title":"","email":"","phone":"","box":"","address_line_1":"","address_line_2":"","location":""},"social_media":{"toggle_visibility":false,"facebook_url":"","instagram_url":"","linkedin_url":"","twitter_url":"","youtube_url":""},"blog_archive_sidebar_visibility":false},"yoast_head":"\nPredicting\u00a0insider trading with AI\u00a0 - 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