After the recent incidents of corporate fraud compounded by one of the worst periods of economic turbulence, there is a need to improve the levels of assurance provided over business activities. The need for internal audit, a profession dedicated to providing assurance, is greater than ever, and internal auditors’ role is taking centre-stage within organisations. These demands have created significant pressure on internal auditors to re-evaluate their approach and methods for evaluation.
Traditionally, the internal audit processes involved a cyclical auditing approach where, having performed an assessment of a process at a particular point in time, reliance is placed on the presumed effectiveness of the process throughout a period, backed by some limited compliance and substantive testing.
Today, the profession is faced with higher costs and longer timelines to provide the required level of assurance, as auditors need to examine the existence and effectiveness of controls in key transactions covering larger periods.
How can internal audit achieve this higher level of assurance? The answer lies in data analytics technology. Comprehensive transactional analysis identifies and reduces instances of fraud/error and increase efficiency of the audit process and, most importantly, provides direct benefits to the bottom-line of an organisation.
Take the case of this telecom giant, which was facing issues with its procurement transactions after it ramped up its cellular tower capacity. This involved both procurement of material, labour and other services from vendors across the country, creating a large volume of procurement transactions to review in a limited timeframe.
Completing this mammoth task in a stipulated timeline was done by deploying data analytics which enabled collation, comparison and verification of transactions across the country for reasonableness and pricing. Designing a batch of standard analytic rules to apply on the entire transaction set helped in identifying critical and high-risk transactions for detailed review. This method enabled easy identification of price mismatch, PO splitting to subvert the approval system and excess procurement of material, which could have been missed following the traditional method.
In another interesting case, a software company that employed more than hundred-thousand people worldwide ran a very large payroll system and implemented a new payroll system. On a closer look at the payroll transactions of the company by deploying data analytics, internal auditors were able to compare payroll processed to attendance and time records of employees for the entire payroll.
A system flaw was detected which made the system pay out? employees for an additional month after they resigned. This helped address a gap which could have resulted in wrong payouts in millions of rupees for the company. While there is a compelling case of deploying analytics, there exists a gap between the widely-accepted ideal and real-world execution. What is preventing audit from more widespread use of analytics? Successfully incorporating analytics into the audit process takes time, skills and resources. The approach requires appropriate technology. However, successful use of analytics is clearly not just about technology: the people and process aspects are equally critical.
With the advent of low-cost computing and data storage, analytics has reached its golden age. Today corporates depend on data analytics for making management decisions and controlling business processes.
Inventory levels, supply chain and transport routing methods are all results of analytics.
There is, therefore, a definite case for inclusion of larger portions of analytics into internal audit programmes. With greater reliance placed in technology and analytic tools, demand for such assurance is set to increase.