Article Search: Pn. Marziati Md Din (Pegawai Kewangan)
Article by : Jami Shine, CIA, CRMA, CISA, CRISC, Corporate and IT audit manager for QuikTrip Corp. in Tulsa, Okla.
Auditors pride themselves on being objective, a critical trait to meet stakeholder needs. And since audit results are usually based on test results, or data, it’s hard to imagine how a lack of objectivity could impact findings. After all, data is data, right? Unfortunately, it can be easy for even the most seasoned auditor to fall prey to bias, even when taking a data-based approach.
As humans, we tend to see what we expect to see. Sometimes this means not questioning results that are in a “normal” range — such as my blood pressure readings. As auditors, giving in to this line of thinking can limit the value we provide to our clients.
For example, an auditor might perform a standard variance analysis and find that results are comparable to the prior year. However, perhaps that account balance should have changed significantly from the prior year. The lack of change should be a red flag, but an auditor not thinking critically might miss this sign and instead perceive it as an indication that no further testing is needed.
In other instances, auditors may receive inaccurate or incomplete data and that data might provide reasonable enough results that the auditor might fail to perceive that they are missing part of the puzzle.
There are several techniques auditors can use to avoid falling into these traps:
Failure to think critically, validate data, and set reasonable expectations for data analytics results could damage the trust our audit clients have in us. We must be constantly vigilant of our biases so they don’t impact the value we provide as trusted advisors.
Date of Input: 01/03/2024 | Updated: 01/03/2024 | muhammad.isam
Tingkat 2,
Blok F, Bangunan Sekolah Perniagaan dan Ekonomi(SPE),
Jalan Persiaran Tulang Daing,
Universiti Putra Malaysia,
43400 Serdang.