The growth of fintech, particularly in artificial intelligence (AI), machine learning (ML), and blockchain, has significantly impacted the adoption and provision of Islamic financial services today. Important choices, including investments, macroeconomic analysis, and credit assessment, are getting harder in the world of Islamic finance. Financial institutions today use artificial intelligence and machine learning, which greatly impacts the Islamic financial services sector. Machine learning (ML) can reduce operating expenses by automating repetitive tasks and increasing efficiency because financial transaction processes are increasingly complex. Data about Islamic finance will be in significant volume. Massive amounts of data are understood, and meaningful patterns are found within them with the aid of machine learning systems. Then, this information is applied to improve business operations, make wise decisions, and help with the work of prediction.
Islamic fintech and banking clients are increasing due to both the booming Muslim population worldwide and the growing trust of current users. By 2060, there will be over 3 billion Muslims, and most Muslim nations will grow rapidly. Islamic financial assets are anticipated to increase rapidly. This admiration for Islamic fintech is accompanied by certain reservations, too. Enormous human resources, a solid regulatory framework, and a well-defined government strategy are all necessary for such rapid expansion in a fledgling business. As a result, governments and academic institutions are crucial to the future success of Islamic fintech.
Researchers in virtually all sectors of Islamic finance have been amazed by AI/ML's outstanding performance and unsurpassed precision. AI/ML, comprising computational intelligence, deep learning, and reinforcement learning, has arisen as a fresh phenomenon. The use of AI and ML in the revival of Islamic Finance is so pervasive that it has the potential to theoretically and practically provide solutions to every issue from every industry. In other situations, it went beyond human intelligence and cognition, coming very close to it. This modern tsunami affects all industries, including the BFSI (banking, finance, and insurance) sector. Computational intelligence, deep learning, deep reinforcement learning, and conventional ML-based predictive analytics are all included in these technologies.
This book's primary goal is to comprehensively understand the functions of AI and ML algorithms in the financial sectors, focusing on Islamic finance, Banking, and the Capital market. Additionally, it intends to offer a compendium of excellent research papers that tackle major issues in AI's theoretical and practical applications in the Islamic finance industry. We ask coworkers to submit original book chapters that will encourage ongoing work on ML algorithms that help tackle the huge massive data processing challenge in a complicated Islamic banking and financial environment. Practitioners creating algorithms, systems, and applications are also encouraged to discuss their ideas, experiences, and findings.