Teaching Note—Data Science Training for Finance and Risk Analysis: A Pedagogical Approach with Integrating Online Platforms

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The main discussion of this paper is a method of data science training, which allows responding to the complex challenges of finance and risk analysis. There is growing recognition of the importance of creating and deploying financial models for risk management, incorporating new data and Big Data sources. Automating, analyzing, and optimizing a set of complex financial systems requires a wide range of skills and competencies that are rarely taught in typical finance and econometrics courses. Adopting these technologies for financial problems necessitates new skills and knowledge about processes, quality assurance frameworks, technologies, security needs, privacy, and legal issues. This paper discusses a pedagogical approach to overcome the teaching complexity of needed soft and hard skills in an integrated manner with its advantages, disadvantages, and vulnerabilities.
Original languageEnglish
Title of host publicationStatistical Modelling and Risk Analysis
Subtitle of host publicationSelected contributions from ICRA9, Perugia, Italy, May 25-27, 2022
EditorsChristos P. Kitsos, Teresa A. Oliveira, Francesca Pierri, Marialuisa Restaino
Place of PublicationGewebestrasse, Switzerland
PublisherSpringer Nature
Number of pages8
ISBN (Electronic)978-3-031-39864-3
ISBN (Print)978-3-031-39863-6
Publication statusPublished - 13 Dec 2023
Event9th International Conference on Risk Analysis (ICRA9) - The University of Perugia and the University of Salerno, Perugia, Italy
Duration: 25 May 202227 May 2022
Conference number: 9th

Publication series

NameSpringer Proceedings in Mathematics & Statistics
PublisherSpringer Nature
ISSN (Print)2194-1009
ISSN (Electronic)2194-1017


Conference9th International Conference on Risk Analysis (ICRA9)
Abbreviated titleICRA9
Internet address


  • Data Science
  • Finance
  • Risk Analysis
  • Active Learning
  • Big Data


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