American Journal of Data Mining and Knowledge Discovery

Special Issue

Wider Thoughts on the Application of Data Mining Tools and Predictive Modelling in Finance

  • Submission Deadline: Dec. 20, 2020
  • Status: Submission Closed
  • Lead Guest Editor: Leonard Mushunje
About This Special Issue
This issue is intended to publish papers in the related field of finance which portrays an idea of data mining and big data analytics. Data mining is a concept which is applied to big data so as to draw hidden patterns and to draw significant conclusions from such patterns. These patterns maybe of great use in the field of finance and economics if treated in a good manner which we want to emphasis on. For great instance, visible and powerful decisions can be made based on such patterns up to the level of sustaining and supporting the survivability of firms in Finance. Of course finance is a broad subject but data mining seem to be relevant due to short time increases of data within the field and other related areas like investment, economics, online trading among others. This issue at large aims to apply data mining tools, mathematics, statistics and physics modeling techniques to make some useful predictive modelling. We are sure these applications to finance are of noble use. Therefore, this issue is welcoming all related articles and contributions for publication.
Aims and Scope:
  1. Application of data mining tools to finance.
  2. Application predictive models to financial economics.
  3. Risk management, actuarial decision makings, insurance and accounting procedures involving big data to be set and led at a better pace with new modelling developments that makes everything easy with high quality
  4. Financial market movement analysis improvement and in-depth analysis.
  5. The unfailing role of big data on business life and decision making processes using big data available.
  6. To bring the value and role of Data scientists and analysts, mathematicians and Quants on clear and open ground.
Lead Guest Editor
  • Leonard Mushunje

    Department of Applied Mathematics, Midlands state university, Senga, Zimbabwe

Guest Editors
  • Maxwell Mashasha

    Midlands State University, Gweru, Zimbabwe

  • Cyril Murewi

    Midlands State University, Gweru, Zimbabwe

  • Fastel Chipepa

    Midlands State University, Gweru, Zimbabwe

  • Marx Dambaza

    Midlands State University, Senga, Zimbabwe

  • Adrian Mutize

    Midlands State University, Senga, Zimbabwe

  • Charlom Magwaniza

    Nyahuni Adventist High School, Murehwa, Zimbabwe

Published Articles
  • Fraud Detection and Fraudulent Risks Management in the Insurance Sector Using Selected Data Mining Tools

    Leonard Mushunje

    Issue: Volume 4, Issue 2, December 2019
    Pages: 70-74
    Received: Oct. 02, 2019
    Accepted: Nov. 06, 2019
    Published: Nov. 19, 2019
    DOI: 10.11648/j.ajdmkd.20190402.13
    Abstract: Knowledge discovery, shortly known as Data mining plays a crucial role within the insurance sector. Serious troublesome cases such as fraudulent cases can be well managed in the insurance sector through data mining application. In this paper, we aim to put on surface the two forms of fraud that is softy and hard fraud, to give out the causes of suc... Show More