Using improved agglomerative hierarchical technique to rationalize investment decisions in Iraqi banks

Abstract EN

The banking system relied on many decisions and is usually made manually, because of the large volume of data, the long time it takes to make a decision, and the possibility of a major error.

Banks are now turning to data mining tools to predict payment delays, detect illegal transactions, record and approve credits, and more.

In this paper, the researcher adopts the Improved Agglomerative Hierarchical Clustering of the classification of ethnic banks based on their annual profits for the period (2012-2015), to enable the investor to make the decision to invest his money in a bank that achieves great profits.

The original algorithm was compared with the improved algorithm, and the results showed an improvement in execution time by 35 % .