Key audit matters and how audit procedures respond to each matter are described below. Allowance for expected credit loss on loans to customers As discussed in Note 14 to the consolidated financial statements, as at 31 December 2021, the Group had loans to customers of Baht 57,836 million (accounting for 41 percent of total assets) and allowance for expected credit loss of Baht 2,615 million, which are material to the financial statements. In determining an allowance for expected credit loss, the Group has developed models to calculate the allowance for expected credit loss, the models required complex calculation and involves significant judgements and estimates from the management. The areas of significant management’s judgement include the identification of criteria for a significant increase in credit risk since initial recognition, the probability of default, the loss given default, the exposure at default, the calculation of expected credit loss, the selection of future economic variables to be incorporated into the models and the management overlay adjustment to the allowance for expected credit loss due to limitations of the models. Because of the significant and the extent of judgement and estimates, I addressed the adequacy of the allowance for expected credit loss of loans to customers as a key audit matter. I gained an understanding of, assessed and tested, on a sampling basis, the effectiveness of internal controls relevant to the loan origination and collection processes, the assessment of probability of default, loss given default and exposure at default, as well as the calculation of allowance for expected credit loss, and tested, on a sampling basis, internal control systems over the relevant information technology systems. In addition, I evaluated and tested the reasonableness of the expected credit loss models, the rules and criteria applied by the Group in the assessment of significant increases in credit risk since initial recognition, including the data used in the model design, the effectiveness of models for significant loan types and the governance process over the model development, by examining model development documentation, testing, on a sampling basis, the accuracy and completeness of data used in model development, and assessing the methods and assumptions applied in the calculation. I assessed the reasonableness of macroeconomic factors and probability of different scenario weights as well as the reasonableness of the management overlay adjustments. I compared accounting policies of the Group with financial reporting standards and assessed the adequacy of disclosure in accordance with the relevant financial reporting standards. Moreover, I examined the allowance for expected credit loss by testing, on a sampling basis, the classification and recalculating the allowance for expected credit loss as at the end of the accounting period, including testing the completeness of data used in the calculation of allowance for expected credit loss. Recognition of interest income For the year 2021, the Group recognised interest income on hire-purchase and financial lease receivables amounting to Baht 3,430 million (accounting for 18 percent of total income). The Group recognises interest income using the effective interest rate method, and interest income is generated from loans provided to a large number of customers with a high volume of transactions. I therefore focused my audit on whether interest income on loans to customers is recognised correctly, appropriately and in a timely manner, in accordance with Thai Financial Reporting Standards. I gained an understanding of, assessed and tested, on a sampling basis, the effectiveness of internal controls relating to the processes of loan origination, interest income recognition and loan collection, including relevant internal controls over information systems, by inquiring of management to gain an understanding, assessing the methods applied by the management, as well as testing, the accuracy of data and calculation. In addition, I applied a sampling method 204
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