Objective - The disruption has been occurring in financial services. Thus, rethinking a new strategy for banking is needed to make a sustainable innovation in organizations. Studies mentioned that formulating strategy is a very costly, time-consuming, and comprehensive analysis. The purpose of this study is to present an integrated intelligence algorithm for estimating the bank's strategy in Indonesia.

Methodology – This study used the integration model between two modules. The algorithm has two basic modules, called Artificial Neural Network (ANN) and Analytical Hierarchy Process (AHP). AHP is capable of handling a multi-level decision-making structure with the use of five expert judgments in the pairwise comparison process. Meanwhile, ANN is utilized as an inductive algorithm in discovering the predictive strategy of the bank and used to explain the strategic factors which improved in forward.

Findings and Novelty – The empirical results indicate that ANN and AHP integration was proved to predict the business strategy of the bank in five scenarios. Strategy 5 was the best choice for the bank and Innovate Like Fintechs (ILF) is the most factor consideration. The strategy choice was appropriate for the condition of the bank's factors. This framework can be implemented to help bankers to decide on bank operations.

Type of Paper - Empirical

Keywords: Bank's strategy, ANN, AHP, BSC, Indonesia.

JEL Classification: M15, O32

URI: http://gatrenterprise.com/GATRJournals/JFBR/vol5.4_1.html

DOI: https://doi.org/10.35609/jfbr.2021.5.4(1)

Pages 01 – 09