AI-Driven Financial Risk Prevention: the Role of HR Analytics in Corporate Crisis Management Under Industry 5.0

This paper addresses a persistent research gap: existing financial-distress models rely almost exclusively on ex post accounting ratios, overlooking human-capital variables that often signal crises much earlier. We propose an Artificial Intelligence (AI)-driven framework that integrates HR analytics with financial indicators under the Industry 5.0 paradigm. The pipeline combines machine learning, NLP, federated learning and blockchain-based auditability, producing a legally compliant and explainable early-warning system. Using a harmonised dataset of 50 European SMEs (2019–2024), the model achieves an AUROC of 0.92 and reduces false positives by nearly 50% compared to Altman-based triggers. A comparative analysis with traditional credit-scoring and CAMEL ratios confrms a 25–30% improvement in forecasting crises 6–12 months in advance. Governance mechanisms—AI committees, audit logs and human-in-the-loop oversight—embed EU regulatory requirements (AI Act, Data Act, DGA) and ensure transparency, accountability and worker protection. The study provides actionable insights for managers, highlighting how turnover and skill gaps anticipate liquidity shocks, thereby linking workforce planning to financial resilience in Industry 5.0 organisations.