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A store sells goods bundled with vouchers granting discounts on future purchases. Under Ind AS 115, revenue must be allocated between the goods and the voucher based on stand-alone selling prices, which requires estimating the likelihood of voucher redemption. How can Machine Learning assist?
AML eliminates the Ind AS 115 requirement to estimate redemption probability altogether
BML automatically classifies the voucher as a separate sale, bypassing the allocation requirement
CML can analyse historical customer behaviour to produce a more realistic redemption-probability estimate, improving the revenue allocation
DML is restricted to fraud detection and cannot be used in revenue estimates
Answer & Solution
Correct answer: C. ML can analyse historical customer behaviour to produce a more realistic redemption-probability estimate, improving the revenue allocation
The chapter explicitly cites this Ind AS 115 voucher example as a case where predictive ML models track customer preference and improve the estimate of redemption likelihood. The Ind AS 115 requirement to estimate is not eliminated — its inputs become more accurate.
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