Development of Indonesian Islamic Banking Financial Inclusion Strategy: A Machine Learning Approach

Islamic banking in Indonesia has a lower financial inclusion index and profitability than the total banking industry, despite its continuous growth. With better resilience to the crisis, the importance of financial inclusion to the economy, and the dependence on financing income, Islamic banking should increase profitability and play an important role in increasing financial inclusion through financing growth. Despite being widely discussed, predictive analytics with machine learning has not been commonly used in developing banking strategies. This study introduces the use of predictive analytics with machine learning to develop strategies for increasing and aligning the financial inclusion and profitability of Islamic banks in Indonesia through financing, with financial analysis as a feedback mechanism. The study results in the strategy recommendation for Islamic banking to focus on MSME and Consumer financing to increase financial inclusion and profitability concurrently. The research also demonstrates that predictive analytics with machine learning and financial analysis can be used in developing financial inclusion strategies for Islamic banks, with the need for intervention to grow MSME working capital financing. The study is expected to become a new reference in developing strategies to increase Islamic banking's financial inclusion and profitability.