Prediction of Mergers and Acquisitions in US Banking: A Data Analytics Framework

• In Event: OPERATIONS FINANCE INTERFACE: Application of AI in Financial Services

Abstract

Merges and acquisitions (M&As) are widely used strategies by banks to grow and maintain their position in the financial market. In this study we aim to utilize data mining and machine learning approaches to develop interpretable predictive models that are capable of predicting the occurrence of M&As in the banking system in the United States. In addition, we aim to discover the important contributing factors that are of importance for M&As. We utilize both micro/macro-economic data and bank fundamentals for the analysis. We believe that our findings may assist banks in order to make strategic data-driven decisions regarding M&As.

Authors

• Zahra Sedighi-Maman, Adelphi University

• Jonathan J Heath, Georgetown University

• Senay Acikgoz, Ankara Hacı Bayram Veli University

• Cem Karatas, Adelphi University