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AI-Driven Product Recommendation Systems for Participation Banking Enhancing Customer Engagement Within Islamic Finance Principles
Abstract
ABSTRACT This study explores the application of artificial intelligence (AI) in participation banking to enhance customer engagement and satisfaction through targeted product recommendations, aligned with the principles of Islamic finance. A random sample of CRM data was analyzed using clustering through the K-Means algorithm, followed by association analysis with the FP Growth algorithm.. This model enables participation banks to provide personalized, compliant product recommendations that increase customer activity and loyalty. Results indicate that machine learning techniques can offer valuable insights into customer behavior patterns, allowing banks to enhance their service offerings while adhering to Islamic finance principles. By supporting customer-centered service delivery, this AI-driven approach contributes to sustainable growth within the participation banking sector.
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