The dissertation substantiates theoretical foundations and practical directions for improving forensic diagnostics and auditing under fraud risks and regulatory turbulence.
Forensic diagnostics is studied as a component of the analytical support for the audit of business entity activities. Approaches to fraud identification, assessment, and prevention are determined; the role of forensic diagnostics as a systemic tool of management analytics for ensuring the economic security of enterprises is substantiated. Innovative directions for integrating forensic diagnostics into the audit system are proposed, considering the requirements of the regulatory environment.
Forensic diagnostics is conceptualized as a systemic tool for analytical audit support. Its functions, application principles, and analytical capabilities in the modern economic environment are defined. The relevance of institutional formalization and implementation of forensic diagnostics into management processes is substantiated to ensure business transparency.
The foundations of forensic diagnostics as an interdisciplinary field integrating auditing, crisis management, financial analytics, forensic economic expertise, and information technology are revealed. The role of forensic diagnostics as a mechanism for supporting management decision-making in risk prevention is proven. An original approach to activity assessment aimed at detecting destructive influences and ensuring stakeholder trust is proposed.
The influence of institutional and informational environments on the development of forensic diagnostics is analyzed. Economic, legal, and technological drivers for implementing forensic tools in audit practice are identified. It is established that under digitalization, forensic diagnostics enables timely response to risks, enhances investor confidence, and ensures proper corporate governance.
An organizational and information model of forensic diagnostics is developed, including analytical, procedural, and managerial components integrated into a unified anti-crisis response framework. The role of forensic diagnostics is defined as a tool for enhancing transparency and accountability in managerial decision-making. Implementation of this model ensures identification of fraud risks, the formation of an evidence base, and strengthening economic security.
The feasibility of applying the praxeological approach based on the axiom of purposeful behavior of economic agents is substantiated. This approach implies considering the behavioral characteristics of the business entity personnel. Such a paradigm enhances the accuracy of analytical conclusions, ensures identification of atypical actions and assessment of the impact of human factors on performance results.
The integration of survey methods, behavioral analytics, and machine learning algorithms into the process of detecting fraud indicators is substantiated. The effectiveness of models in identifying anomalous transactions and reducing financial risks is proven. A KPI system adapted to the digital economy is developed, enabling performance comparisons among enterprises regardless of scale.
An implementation procedure for digital analysis is proposed, including digital architecture development, a digital hub for data aggregation (ERP, CRM, POS), development of interfaces with analytical tools (BI, clustering, anomaly detection), and the formation of a technological environment with cybersecurity measures.
Attention is given to the development of digital competencies of personnel regarding the interpretation of analytical findings and integrating data into planning. The procedure ensures the relevance of decision-making, contributing to increased business model resilience and responsiveness to changes in the digital environment.
The practical significance lies in developing innovative approaches to forensic diagnostics and audit. The proposed transaction clustering model using K-Means and Isolation Forest methods enables real-time detection of atypical operations, improving the accuracy of fraud diagnostics.
An integrated matrix of risk indicators synchronized with IT systems (ERP, CRM, POS) is developed, providing automation of internal control. Methodological unity of traditional audit and artificial intelligence is ensured within the Audit-Forensic Diagnostic Support Method (AFDSM).
Implementation of the approaches is confirmed by the adoption of results in retail chains and consulting companies. The praxeological approach allows for considering behavioral aspects of management, improving client loyalty, and ensuring strategic sustainability of the business model.
