Corporate Fraud in Finance & Risk Management Forensic Accounting and Fraud Detection Techniques - Moving from Reactive to Predictive Fraud Detection

Abstract:

In India, corporate fraud is a serious concern. The RBI has registered a 28% rise in cases of bank fraud and a 159% increase in the amount of money siphoned off during 2019-20. The most common examples of scams include Satyam (2009) and Nirav Modi (2018). In both the cases, the scams were detected after it had happened. There is a dearth of literature on proactive fraud risk management in India. Objectives of the study: The present study is an attempt to discuss the various tools and techniques to detect accounting manipulation, deceit, and fraud in financial statements and its Cartesian geometry.

In addition, the study is an effort to explore the role of forensic accounting and analytics in corporate fraud risk management. The study proposes a predictive model for fraud detection, auditor decision making matrix, and early warning signals, customized to Indian corporate scenario.

The study uses mixed methods research approach. First, a quantitative study has been conducted to review 200 fraud cases (1991-2025) to find out the fraud patterns. Second, a qualitative study has been done by conducting interviews with 50 stakeholders, analyzing 116 Indian theses and 200 judicial orders (2017-2024) to identify the vulnerabilities and trends using thematic coding principles similar to NVivo qualitative analysis. Significance of the study: In the light of current and emerging developments such as AI-generated fraud, this study bridges the forensic gap to help India’s financial systems to respond effectively. The study ensures data privacy and observes legal standards of conducting research.