Application of Data Mining Technology in Financial Risk Analysis

Facing the cruel market competition environment, the enterprise’s demand for risk management is increasing day by day. How to objectively evaluate the financial risks existing in the process of enterprise management and how to timely warn them is the goal that the enterprise management always pursue...

Full description

Saved in:
Bibliographic Details
Published in:Wireless personal communications 2018-10, Vol.102 (4), p.3699-3713
Main Authors: Jin, Maozhu, Wang, Yanan, Zeng, Yucheng
Format: Article
Language:English
Subjects:
Algorithms
Communications Engineering
Computer Communication Networks
Data mining
Engineering
Financial management
Networks
Risk analysis
Risk management
Signal,Image and Speech Processing
Technology assessment
Uncertainty
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Facing the cruel market competition environment, the enterprise’s demand for risk management is increasing day by day. How to objectively evaluate the financial risks existing in the process of enterprise management and how to timely warn them is the goal that the enterprise management always pursues. Enterprise financial risk analysis and early warning research is influenced by various factors inside and outside the enterprise. The results show that the uncertainty of the technology is very high, and the excellent performance of data mining technology in the study of uncertainty theory links the two closely. In addition, it also proves that the three improved algorithms of association rules greatly improve the efficiency of data mining. Meanwhile, the concept hierarchy tree model of enterprise financial risk and the financial crisis early-warning model of dynamic maintenance of time series are put forward. In conclusion, these algorithms are suitable for the research of enterprise financial risk analysis and crisis warning.
ISSN:0929-6212
1572-834X
DOI:10.1007/s11277-018-5402-5