Blitz Bureau
NEW DELHI: India Inc is witnessing a decisive shift in the way companies monitor their operations, driven by a marked rise in financial fraud, rapid digitisation and the expanding influence of artificial intelligence.
The long-standing practice of periodic internal audits — conducted quarterly or annually — is increasingly seen as inadequate for a digital ecosystem where risks emerge and escalate in real time.
A recent survey by PwC underscores the urgency of this transition. It found that 59 per cent of Indian organisations experienced financial or economic crime in the past two years, significantly higher than the global average.
Fraud typologies have also evolved, with procurement fraud overtaking customer fraud as the most prevalent threat. This trend, auditors caution, reflects not only operational lapses but also the growing sophistication of fraudsters who understand how to exploit weak or outdated internal controls.
Sample-based approach
For decades, internal audits relied on sampling methods and time-bound reviews. However, the explosion of data volumes, the rise of interconnected ERPs and cloud-based systems, and the shift toward automated processes have exposed the inherent limitations of this approach.
Traditional audits often flag irregularities long after the act. As Sunil Bhadu, India GRC Leader at PwC, notes, the conventional model lacks the agility that today’s business environment demands. “Static reviews cannot keep pace with real-time operational risks or the speed at which digital transactions occur,” he said.
This has led many organisations to adopt continuous controls monitoring (CCM) — a technology-driven framework that tracks transactions and system behaviour round the clock. Unlike sample-based testing, CCM examines 100 per cent of data, enabling early detection of anomalies and faster corrective action.
AI as both enabler and challenge
Artificial intelligence is becoming central to this transformation. Advanced analytics and machine-learning tools now support internal audit teams in reviewing vast amounts of information, identifying suspicious patterns, and predicting potential vulnerabilities.
Yet AI is not without its complications. Regulators globally have raised concerns about algorithmic bias, opaque decision-making and the risk of data leakage. A recent review by the UK’s Financial Reporting Council found that audit firms often lack clarity on how AI tools affect audit quality — a warning that Indian firms are taking seriously.
Audit committees are therefore placing equal emphasis on technology adoption and governance frameworks that ensure accuracy, fairness and accountability in AI-assisted audit processes.
Regulatory push
The regulatory ecosystem is reinforcing the shift toward real-time audit. India’s CERT-In has recommended continuous compliance monitoring, while the Reserve Bank of India has urged financial institutions to deploy AI-led surveillance to identify service failures and financial irregularities early.
India’s participation in a global AI / ML audit initiative, involving 29 countries, further signals commitment to modernising oversight mechanisms.
Although the transition to real-time audit will require sustained investment and capability-building, experts argue that its long-term benefits — early detection of fraud, stronger governance and enhanced organisational resilience — far outweigh the costs.