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All Journal SAINSTECH: Jurnal Penelitian dan Pengkajian Sains dan Teknologi
Suhaunan, Zaldi
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Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering Engineering Mechanical Engineering

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Sinergi AI dan Automatisasi CRM untuk Mencegah Churn Nasabah pada Bank Konvensional Handijono, Ardijan; Suhaunan, Zaldi
SAINSTECH: JURNAL PENELITIAN DAN PENGKAJIAN SAINS DAN TEKNOLOGI Vol. 35 No. 3 (2025): Sainstech : Jurnal Penelitian dan Pengkajian Sains dan Teknologi
Publisher : Institut Sains dan Teknologi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37277/stch.v35i3.2394

Abstract

In the banking industry, where aggressive competition from digital banks poses a growing threat, customer retention is no longer just a business strategy -it's a prerequisite for long-term profitability. This study unveils a revolutionary approach to mitigate customer churn through the synergy of AI-based churn prediction and CRM automation. By analyzing historical transaction data from Bank XYZ, we developed a machine learning model that not only accurately identifies high-risk customers but also automatically triggers personalized retention interventions. Through a rigorous A/B test experiment, we proved that this proactive approach results in a phenomenal reduction in churn rates. The study's findings show a proactive intervention success rate of 73.68%, a figure that significantly surpasses conventional retention methods. This finding not only solidifies the vital role of AI in business decision-making but also paves a new path for the banking industry to build efficient, proactive, and sustainable retention strategies in the digital era. Keywords: Customer Churn, Machine Learning, Customer Retention, CRM Automation
Co-Authors Handijono, Ardijan