Predicting the success of mergers in the Banking industry

Literature pertaining to prediction of takeover targets in the Banking industry is aplenty. Typically, a set of functioning banks in the region of interest with the accounting information for each of the banks were utilized to predict targets. The research was generally aimed at banks to assess their likelihood of being acquired. The proposed research however aims at developing a quantitative financial model using M&A (Merger and Acquisition) data of mergers, for prediction of the probability of success of a prospective merger. The best quantitative prediction model using Principle Component Analysis coupled with Artificial Neural Networks is formulated after the comparison of various classification techniques.