INNOVATIVE TECHNOLOGIES IN RISK MANAGEMENT: THE ROLE OF ARTIFICIAL INTELLIGENCE IN THE IDENTIFICATION AND MITIGATION OF CORPORATE FINANCIAL RISKS

Resumo

The rapid pace of digital transformation has significantly reshaped financial risk management, with Artificial Intelligence (AI) emerging as a strategic tool to enhance accuracy, agility, and security in corporate decision-making. This study, classified as a qualitative, exploratory, and descriptive bibliographic research, investigates how AI has been applied to the identification and mitigation of corporate financial risks, emphasizing its contributions to compliance, fraud detection, and strategic decision support. The investigation was based on the systematic review of academic works retrieved from renowned databases, namely CAPES Periódicos, ResearchGate, Scopus, and Web of Science, focusing on publications between 2020 and 2025. The qualitative approach allowed for an in-depth analysis of concepts, applications, benefits, and limitations presented in the literature, aiming to interpret and synthesize the main theoretical and practical contributions. AI’s operational benefits include automation of routine tasks, real-time data processing, predictive analytics, and improved regulatory compliance, thereby reducing human error and operational costs. Furthermore, AI enables continuous monitoring, identification of anomalous patterns, and prevention of fraudulent activities through machine learning algorithms and neural networks, enhancing organizational resilience and strategic foresight. However, the adoption of AI in risk management is not free from challenges, as it demands substantial investments in technology infrastructure, high-quality data, skilled professionals, and the overcoming of cultural, ethical, and technical barriers. Issues such as algorithm transparency, compliance with data protection laws, and prevention of bias in automated decision-making are critical to ensuring stakeholder trust and regulatory conformity. The integration of AI with governance frameworks and Total Quality Management (TQM) principles strengthens corporate transparency, optimizes internal processes, and fosters a culture of continuous improvement in risk management practices. The literature review indicates that, when effectively implemented, AI can deliver sustainable competitive advantages by enabling organizations to anticipate threats, respond proactively to emerging risks, and align strategic decisions with long-term objectives. Nevertheless, the success of AI adoption depends on aligning technological capabilities with organizational culture, promoting continuous workforce training, and ensuring ethical and regulatory compliance. In conclusion, AI represents a transformative opportunity for corporate financial risk management, offering tools to not only identify and mitigate risks with greater precision but also to redefine operational and strategic paradigms in the financial sector. Its successful implementation requires an integrated approach that balances innovation, governance, and human oversight, ensuring that technological advances contribute to building robust, transparent, and future-oriented organizations.