ABSTRACT
Financial fraud and audit inadequacy represent two of the most formidable challenges facing Indian businesses today. Rajasthan—India's largest state by area and a rapidly industrialising economy with over 4.8 lakh registered MSMEs—presents a particularly compelling context for studying the adoption and impact of Artificial Intelligence (AI) and Data Analytics (DA) in audit and fraud-detection functions. This empirical paper draws on a structured primary survey of 320 respondents (auditors, CFOs, internal audit heads, and fintech professionals) across Jaipur, Jodhpur, Udaipur, Kota, and Ajmer, supplemented by secondary data from NCRB (2023), PwC's Global Economic Crime Survey India 2024, IMARC Group, BioCatch India, and ICAI publications. Statistical analysis employs descriptive statistics, chi-square tests, Pearson correlation analysis, one-way ANOVA, regression modelling, and a Technology Adoption Scorecard to examine the determinants and outcomes of AI/DA adoption in audit and fraud-detection workflows. Findings reveal that Rajasthan tops national financial fraud case registers (27,675 cases in 2023 per NCRB), yet AI adoption in audit functions remains nascent—particularly among MSMEs and tier-2 city practitioners. Organisations that have deployed AI tools report average audit cycle time reductions of 43%, false-positive rates in fraud alerts declining from 42% to 11%, and detection accuracy improvements of 35–68 percentage points. The paper proposes a 'SMART-Audit Framework' for phased AI integration tailored to Rajasthan's economic structure and concludes with policy recommendations for ICAI-Rajasthan Chapter, RIICO, and the state government.
Keywords: Artificial Intelligence, Data Analytics, Audit Efficiency, Fraud Detection, Rajasthan, MSME, Machine Learning, RPA, NCRB, Forensic Audit, ICAI, India.