AUTOMATING COMPLIANCE: ROLE-BASED LEARNING TECHNOLOGIES IN FINANCIAL SERVICES RISK MANAGEMENT - Priyesh Rajasekaran (INTERNATIONAL JOURNAL OF ENGINEERING AND TECHNOLOGY RESEARCH (IJETR), 2024)
In today's complex regulatory environment, financial institutions face significant challenges in maintaining a compliant workforce. Traditional compliance training methods often prove inadequate, leading to disengagement and knowledge gaps that can expose organizations to substantial risks. This article explores the transformative potential of learning technologies in revolutionizing compliance training within the financial services sector. We present a comprehensive framework for implementing automated, role-based learning systems that identify and prioritize compliance risks, create personalized learning pathways, and leverage AI-driven platforms to streamline training delivery and tracking. Through a critical analysis of case studies and empirical data, we demonstrate how this technology-driven approach not only enhances knowledge retention and employee engagement but also significantly improves an organization's ability to mitigate regulatory risks. The article addresses key implementation challenges, including data privacy concerns and change management strategies, while providing actionable insights for financial institutions seeking to cultivate a robust culture of compliance. Our findings suggest that by adopting these innovative learning methodologies, organizations can more effectively navigate the complexities of the regulatory landscape, reduce compliance-related incidents, and foster a workforce that is both knowledgeable and adaptable to evolving regulatory requirements.