e-ISSN 2231-8526
ISSN 0128-7680
Sameer, F. and Abu Bakar, M. R.
Pertanika Journal of Science & Technology, Volume 25, Issue 1, January 2017
Keywords: Credit Scoring, Decision-making, Clustering Techniques, Fuzzy Clustering Algorithms, Gustafson-Kessel Algorithm, Kohonen Network
Published on: 31 JANUARY 2017
Credit risk assessment has become an important topic in financial risk administration. Fuzzy clustering analysis has been applied in credit scoring. Gustafson-Kessel (GK) algorithm has been utilised to cluster creditworthy customers as against non-creditworthy ones. A good clustering analysis implemented by good Initial Centres of clusters should be selected. To overcome this problem of Gustafson-Kessel (GK) algorithm, we proposed a modified version of Kohonen Network (KN) algorithm to select the initial centres. Utilising similar degree between points to get similarity density, and then by means of maximum density points selecting; the modified Kohonen Network method generate clustering initial centres to get more reasonable clustering results. The comparative was conducted using three credit scoring datasets: Australian, German and Taiwan. Internal and external indexes of validity clustering are computed and the proposed method was found to have the best performance in these three data sets.
ISSN 0128-7680
e-ISSN 2231-8526