A Study on Use of Algorithmic Audit Sampling in Big 4 Companies

Abstract

Test checking is an accepted audit technique that involves testing less than 100 % of the transaction by selecting sample transactions and using analytical procedures on them with an objective to give an opinion whether the financial statements show a true and fair view. It is effective in nature that most times it is possible to give an appropriate opinion on the whole population by studying a well-selected sample representative of the population. This increases the cost benefit of the process making it financially optimized, efficient and reducing the work involved without compromising on the quality of the opinion. Test checking is adopted also since it is practically not possible to check all transactions like in the case of big, listed companies whose number of transactions run in millions. But test checking can only reduce the workload of an auditor, not his liability. Auditor cannot claim that he couldn’t trace frauds since the misleading transactions were not a part of the selected sample. So, the success of the process is highly dependent on proper audit sampling. All the big four companies prominently conducting statutory audit of listed companies do sample selection incorporating variety of sampling techniques coded in an algorithm created inhouse using variety of conditions. This paper studies the Impact of algorithms used in audit sampling by big 4 companies namely PWC, Deloitte, EY, KPMG while conducting statutory audits of listed companies.