Data Mining Techniques Applied in the Financial Industry

Liang Huo, Tao Wang () and Liu Yang
Additional contact information
Liang Huo: Hebei Finance University
Tao Wang: Hebei Finance University
Liu Yang: Hebei University

Chapter Chapter 130 in The 19th International Conference on Industrial Engineering and Engineering Management, 2013, pp 1237-1243 from Springer

Abstract: Abstrat Data mining is the use of various techniques to discover knowledge from massive data, it has wide application and prospect. The article detailed introduction summarizes the concept of data mining, methods, and applications. And analysis, summarizes the application of data mining in the financial field, including trend forecasting, customer relationship management, financial crime detection, risk identification and risk management.

Keywords: Data mining; Financial data; Prediction; Risk identification (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-38427-1_130

Ordering information: This item can be ordered from
http://www.springer.com/9783642384271

DOI: 10.1007/978-3-642-38427-1_130

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().