Automating financial surveillance

Maria Milosavljevic*, Jean Yves Delort, Hachey Ben, Bavani Arunasalam, Will Radford, James R. Curran

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

6 Citations (Scopus)

Abstract

Financial surveillance technology alerts analysts to suspicious trading events. Our aim is to identify explainable false positives (e.g., caused by price-sensitive information in company news) and explainable true positives (e.g., caused by ramping in forums) by aligning these alerts with publicly available information. Our system aligns 99% of alerts, which will speed the analysts' task by helping them to eliminate false positives and gather evidence for true positives more rapidly.

Original languageEnglish
Title of host publicationUser Centric Media - First International Conference, UCMedia 2009, Revised Selected Papers
Pages305-311
Number of pages7
Volume40 LNICST
DOIs
Publication statusPublished - 2010
Event1st International Conference on User Centric Media, UCMedia 2009 - Venice, Italy
Duration: 9 Dec 200911 Dec 2009

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
Volume40 LNICST
ISSN (Print)18678211

Other

Other1st International Conference on User Centric Media, UCMedia 2009
CountryItaly
CityVenice
Period9/12/0911/12/09

Keywords

  • Document categorisation
  • Financial surveillance
  • Machine learning
  • Sentiment analysis

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