Growing Application of Forensic Accounting in Assessment and Control of Financial Crimes

Abstract

Forensic accounting has evolved into a crucial discipline in detecting and preventing financial crimes, particularly in the digital age, where cyber-enabled fraud has intensified. This study examines how forensic accounting techniques have adapted to address modern financial crimes, incorporating artificial intelligence (AI), blockchain technology, and big data analytics. The research aims to evaluate the effectiveness of these advanced tools in fraud detection and financial transparency. A combination of qualitative analysis and statistical evaluation was used in the mixed-methods approach. The results reveal that AI adoption significantly enhances fraud detection rates, with a Pearson correlation coefficient of 0.997 (p-value = 0.00015), confirming a strong positive relationship. Additionally, a linear regression analysis demonstrated an annual increase of 100 fraud cases from 2020 to 2024, highlighting the growing need for forensic interventions. The chi-square test (χ² = 25.95, p = 0.001) indicates a statistically significant shift in financial crime patterns over time, emphasizing the necessity for continuous advancements in forensic methodologies. The study concludes that forensic accounting, integrated with AI-driven analytics, predictive modeling, and blockchain auditing, significantly improves fraud detection efficiency, increasing from 60% in 2020 to 80% in 2024. To further enhance fraud prevention, organizations should invest in AI-powered forensic tools, strengthen regulatory compliance measures, and promote interdisciplinary collaboration between forensic accountants, cybersecurity experts, and regulatory bodies