Tech savvy workout for CAs on trail of corporate frauds

shailesh agarwal (professional accountant) (7642 Points)

30 December 2008

26 Dec 2008, 0149 hrs IST, ET Bureau

NEW DELHI: Accounting regulator Institute of Chartered Accountants of India (ICAI) has launched a training programme for chartered accountants in

quick data analysis through computer-assisted audit techniques (CAATs). The regulator aims to gradually shift manual analysis of data to a computer-aided one, which is faster and more reliable.

The move comes in the wake of a new-generation data analysis system the corporate affairs ministry is implementing to find trends that indicate wrongdoing from the financial data submitted to the government. The ministry calls this new system MCA 21. The move to train CAs will lend effectiveness to the government’s programme.

The idea is to create an expert group of CAs in the country who can understand such computer-aided audit analysis with ease and draw inferences from them. The scheme will see accountants being trained in the use of audit

investigative tools.

These auditors are expected to bridge the gap of professionals who will help track computer-drawn audit data. The ministry’s programme will sniff through the available financial data to detect corporate frauds.

While computer audit can only find effectiveness after most companies make their accounting data computerised, the training is aimed at evolving a qualified set of auditors who can work on such complex network processes. Today, in most large and medium-sized enterprises, there are many business processes that are not driven by computers. Experts say before such computer audit processes are put in place, companies will have to computerise their key data.

Using CAATs, auditors can analyse expense and revenue heads under the financial accounting applications, while under a banking application, the auditor may verify interest payments using the audit software.

The use of audit software ensures total scrutiny of transactions in which there is audit interest and identify erroneous transactions even when data volumes are huge. All this can be done in a fraction of the time required under a manual audit process.