Data-Driven Credit Risk Management and Financial Stability in the Digital Era: Integrating Behavioral Analytics, FinTech Innovations, and Advanced Scoring Models

Abstract

The rapid digitalization of financial systems has fundamentally transformed credit risk management, financial stability assessment, and customer-centric decision-making across global banking and financial institutions. As financial ecosystems increasingly rely on data-intensive technologies, the integration of behavioral analytics, predictive modeling, and advanced credit scoring frameworks has emerged as a critical determinant of institutional resilience and sustainable growth. This study presents an in-depth, theory-driven exploration of data-driven credit risk management in the digital era, drawing strictly from contemporary scholarly works that address project management transformation, FinTech-driven inclusion, customer experience optimization, behavioral analytics, and machine learning-based credit evaluation. The research synthesizes insights from recent studies to examine how behavioral data enhances predictive accuracy in credit risk assessment, how FinTech innovations empower underserved populations, and how advanced analytical models reshape traditional risk management paradigms. A descriptive and interpretive methodological approach is employed to analyze conceptual frameworks, institutional practices, and technological trajectories without relying on mathematical modeling or empirical datasets. The findings reveal that the convergence of behavioral analytics, data-driven decision systems, and digital project management practices significantly improves financial stability monitoring, customer personalization, and institutional efficiency. However, challenges related to data governance, ethical considerations, skill gaps, and organizational resistance remain substantial. The discussion critically evaluates these challenges while highlighting emerging opportunities for integrated risk intelligence systems and inclusive financial architectures. This study contributes to the expanding body of knowledge on digital finance by offering a holistic theoretical foundation that bridges credit risk analytics, customer experience, and strategic project management. It provides actionable insights for policymakers, financial managers, and researchers seeking to navigate the complexities of financial stability in an increasingly data-centric world.