Location
Hilton Hawaiian Village, Honolulu, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2024 12:00 AM
End Date
6-1-2024 12:00 AM
Description
Protecting financial market integrity is a key concern for regulators as disinformation-driven fraud based on financial fake news (FFN) is taking on a significant role in financial market manipulation. While existing research focuses on describing or categorizing financial fraud schemes more broadly, we aim to provide a taxonomy focusing specifically on FFN schemes. Drawing on U.S. Securities and Exchange Commission (SEC) litigation releases and underpinning theoretical tenets, we utilize an iterative taxonomy approach to systematically classify fraudulent FFN schemes. Our contribution is to provide a robust, comprehensive framework that enhances the body of knowledge about the diverse landscape of financial disinformation. The taxonomy provides practical benefits to market participants and market surveillance authorities by its ability to guide the development of fraud detection systems.
Recommended Citation
Rath, Oliver; Haase, Frederic; Melsbach, Johannes; Liu, Jiarun; Lauten, Julia; and Schoder, Detlef, "Analyzing Threats to Financial Market Integrity - A Taxonomy of Financial Fake News Schemes" (2024). Hawaii International Conference on System Sciences 2024 (HICSS-57). 6.
https://aisel.aisnet.org/hicss-57/dg/emerging_topics_in_e-gov/6
Analyzing Threats to Financial Market Integrity - A Taxonomy of Financial Fake News Schemes
Hilton Hawaiian Village, Honolulu, Hawaii
Protecting financial market integrity is a key concern for regulators as disinformation-driven fraud based on financial fake news (FFN) is taking on a significant role in financial market manipulation. While existing research focuses on describing or categorizing financial fraud schemes more broadly, we aim to provide a taxonomy focusing specifically on FFN schemes. Drawing on U.S. Securities and Exchange Commission (SEC) litigation releases and underpinning theoretical tenets, we utilize an iterative taxonomy approach to systematically classify fraudulent FFN schemes. Our contribution is to provide a robust, comprehensive framework that enhances the body of knowledge about the diverse landscape of financial disinformation. The taxonomy provides practical benefits to market participants and market surveillance authorities by its ability to guide the development of fraud detection systems.
https://aisel.aisnet.org/hicss-57/dg/emerging_topics_in_e-gov/6