THE READABILITY OF KEY AUDIT MATTERS PARAGRAPH IN AUDITOR'S REPORT: A STUDY FROM ASEAN COUNTRIES - Dwi Jayanti; Eliza Fatima (Media Riset Akuntansi, Auditing & Informasi, 2023)
The objective of this research is to explore the readability level of the Key Audit Matters (KAM) paragraph as well as its progress since the first time implementation of KAM for financial statements issued by auditors for listed companies in ASEAN countries. KAM paragraph is extracted from an audit opinion issued by a public accounting firm for companies listed in the capital market around ASEAN countries. Following prior research, by using learning curve theory as a basis, this research applies a quantitative approach to evaluate the readability of the KAM and its progress. Readability is measured by using several commonly used linguistic techniques, which are Flesch Reading Ease (FLESCH), Flesch–Kincaid (KINCAID), and Gunning Fog (FOG) measures). In addition to its role in KAM topic-related research, by bringing the perspective to focus more on readability, this research is able to provide new perspectives on the capability of KAM to affect financial statements users' decisions, as well as provide additional insight for the regulator or professional body for public accountant profession on designing the practical support and assistance to enhance the current practice of KAM writing done by the public accountant, as well as insight for the public accounting firm in preparing clearer and readable KAM paragraphs. This research used ASEAN market data as an emerging market and covered up to the recent year auditor's report to study the readability of the KAM paragraph. Despite some inconsistencies in the observation result, we can make an inference that the readability level of KAM produced by auditors for listed entities in ASEAN countries tend to be more difficult to read as number of experiences in issuing it increasing. This pattern is consistently shown when the sample is divided by type of Auditor and country of exchange. However, when the sample is further detailed down by industry sector, inferences is difficult to be made.