Abstract

Enterprise risk management is a well established methodology used in industry. This area relies heavily on risk owners and their expert opinion. In this work, we present an approach to a semi-automated risk detection for companies using anomaly detection. We present various anomaly detection algorithms and present an approach on how to apply them on multidimensional data sources like news articles and stock data to automatically extract possible risks. To do so, NLP methods, including sentiment analysis, are used to extract numeric values from news articles, which are needed for anomaly analysis. The approach is evaluated by conducting interview questionnaires with domain experts. The results show that the presented approach is a useful tooling that helps risk owners and domain expert to find and detect potential risks for their companies.

Original languageEnglish
Pages1-16
Number of pages16
DOIs
Publication statusPublished - 31 Aug 2022
Event Intelligent Systems and Applications - Amsterdam, Amsterdam, Netherlands
Duration: 1 Sep 20222 Sep 2022
https://saiconference.com/IntelliSys

Conference

Conference Intelligent Systems and Applications
Abbreviated titleIntelliSys
Country/TerritoryNetherlands
CityAmsterdam
Period01.09.202202.09.2022
Internet address

Keywords

  • Anomaly detection
  • Predictive analytics
  • Risk management

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