Optimizing Financial Risk Management Through the Integration of Artificial Intelligence Machine Learning and Strategic Human Resource Management to Anticipate Financial Crises and Enhance Corporate Financial Stability

Haris Aulia Rahman (Universitas Mitra Bangsa Jakarta)
Ardilla Ayu Kirana (Sekolah Tinggi Ilmu Ekonomi Indonesia Surabaya)
Moh. Sholeh (Universitas Trunodjoyo Madura)
M.Makhrus Ali (STAI Ibnu Rusyd Kotabumi Lampung)
Joni Devitra (Universitas Dinamika Bangsa)

Mandalika Journal of Business and Management Studies
Vol 4 No 2 (2026): Mandalika Journal of Business and Management Studies

This study examines how the integration of Artificial Intelligence (AI), Machine Learning (ML), and Strategic Human Resource Management (SHRM) can optimize financial risk management to anticipate financial crises and enhance corporate financial stability. The research employs a qualitative library research approach using primary and secondary data collected from books, peer-reviewed journals, scientific reports, and other relevant academic literature. Data were analyzed using content analysis to identify theoretical patterns, conceptual relationships, and emerging trends related to intelligent financial risk management. The findings indicate that AI and ML significantly improve financial forecasting, fraud detection, and risk prediction through advanced predictive analytics, while SHRM strengthens organizational capabilities by developing adaptive leadership, digital competencies, and strategic decision-making. The integration of these technological and organizational resources creates a comprehensive financial risk management framework that enhances organizational resilience and supports sustainable financial performance. The study concludes that combining AI, ML, and SHRM enables organizations to proactively manage financial uncertainty, improve crisis preparedness, and achieve long-term corporate financial stability in an increasingly dynamic business environment.