Application of the Transportation Algorithm for Selecting Bank Merger Partners

After the experience of the 1997 Asian Financial Crisis, the Malaysian government initiated the consolidation of the commercial banking sector with the aim of creating a core group of strong and well capitalized banking institutions. The first phase of the consolidation was completed by the end of 2001. As a result, the number of domestic banks in the commercial banking sector was reduced from a total of twenty to ten anchor banks which were in compliance with minimum capitalization, asset size, and other prudential requirements. More than a decade since the domestic banking sector has been further reduced to merely eight domestically owned conventional commercial banks and these banks have initiated discussions and negotiations to kick start the second wave of consolidation in the commercial banking sector. However, as a result of market sentiments and failure to arrive at a mutual agreement on pricing and other relevant issues, the second wave of the consolidation of Malaysian commercial banks has been postponed to the future. Regardless of when the consolidation of the banking sector occurs, a key success factor for such M and A exercises would be an optimal selection of merger partners. However, selecting bank merger partners is indeed a highly complex and difficult task with numerous quantitative and qualitative issues to be considered. Given these circumstances, the aim of this paper is to develop a quantitative method using Operations Research (OR) techniques to identify potential merger partners that would optimize the key performance parameters in the EAGLES framework. To this extent, the transportation algorithm is used to produce a viable initial selection of merger partners which can then be subjected to more rigorous qualitative considerations before making the final decision.