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ACCT2110 Current liabilities
Creation date：2024-06-01 17:37:14
Belonging category：会计Accounting
Current liabilities

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ACCT2110 


Topic 4: Provisions and Contingencies
Question 1
ABC Ltd enters into a supply agreement with Buyer Ltd on 1 January 2020. The agreement
states that:
• ABC Ltd must supply Buyers Ltd with 100 chairs at a price of $150 per chair.
• If ABC Ltd cannot deliver the chairs on time and under the terms of the contract it must pay
Buyers Ltd a penalty of $12 000.
• The delivery date is 31 March 2020.
ABC Ltd begins manufacturing the chairs on 1 March 2020, but experiences a series of
production problems that result in the production cost of each chair totalling $200 as at 31
March 2020. Assuming the end of ABC Ltd’s reporting period is 31 March.
Required: Briefly explain how ABC Ltd should account for the contract.

Question 2

In each of the following scenarios, explain whether or not ABC Ltd would be required to
recognise a provision.
a) As a result of its plastics operations, ABC Ltd has contaminated the land on which it
operates. There is no legal requirement to clean up the land, and ABC Ltd has no record of
cleaning up the land that it has contaminated.
b) As a result of its plastic operations, ABC Ltd has contaminated the land on which it operates.
There is a legal requirement to clean up the land.
c) As a result of its plastics operation, ABC Ltd has contaminated the land on which it operates.
There is no legal requirement to clean up the land, but ABC Ltd has a long record of cleaning
up land that it has contaminated.

Question 3
Below are three independent situations.
1. In August 2020, a worker was injured in the factory in an accident partially the result of his
own negligence. The worker has sued Wesley Co. for $800,000. Counsel believes it is
reasonably possible that the outcome of the suit will be unfavorable and that the settlement
would cost the company from $250,000 to $500,000.
ACCT2110 Semester 2/2023
2

2. A suit for breach of contract seeking damages of $2,400,000 was filed by an author against
Greer Co. on October 4, 2020. Greer's legal counsel believes that an unfavorable outcome
is probable. A reasonable estimate of the award to the plaintiff is between $600,000 and
$1,800,000. No amount within this range is a better estimate of potential damages than any
other amount.
3. Quinn Ltd is involved in a pending court case and lawyers believe it is probable that Quinn
Ltd will be awarded damages of $1,000,000.
Required
Discuss the proper accounting treatment, including any required disclosures, for each situation.
Give the rationale for your answers.

Problem 1
On 30 June (the reporting day) 2020, ABC Ltd estimates that it will be required to
pay $100 000 in 3 years’ time (30 June 2023) to settle a warranty obligation. The risk‐free
discount rate applied is 5.5%. The probability of cash outflows has been assessed (i.e. adjusted
for risk) in determining the $100 000.
Required
1. How is the provision accounted for at 30 June 2020 and 30 June 2021? Prepare the journal
entries.
2. At 30 June 2022, ABC Ltd re‐estimates the amount to be paid to settle the obligation at the
end June 2023 to be $90 000. The appropriate discount rate remains at 5.5%. How is the re‐
estimation accounted for? Prepare the journal entries.


Problem 2
LMI Ltd is a lawnmower manufacturer. Its reporting period ends 30 June. Following is an
extract from its financial statements at 30 June 2023.
Current liabilities

Provisions

Provision for warranties

$525 000
Non‐current liabilities

Provisions

Provision for warranties

131 004
Note 37 — contingent liabilities
LMI signed an agreement with BankSouth on 3 April 2023 to the effect that LMI guarantees a loan
made by BankSouth to LMI’s subsidiary, LSS Ltd. LSS’s loan with BankSouth was $56 million as at
30 June 2023. LSS was in a strong financial position at 30 June 2023 and accordingly LMI believes
that it is not probable that the guarantee will be called (AASB 137/IAS 37 paragraph 86).
ACCT2110 Semester 2/2023
3


The provision for warranties at 30 June 2023 was calculated using the following assumptions (there
was no balance carried forward from the prior year).
Estimated cost of repairs — products with minor defects $2 000 000
Estimated cost of repairs — products with major defects $5 500 000
Expected % of products sold during FY 2023 having no defects in FY 2024 75%
Expected % of products sold during FY 2023 having minor defects in FY 2024 20%
Expected % of products sold during FY 2023 having major defects in FY 2024 5%
Expected timing of settlement of warranty payments — those with minor defects 90% in FY 2024,
10% in FY 2025
Expected timing of settlement of warranty payments — those with major defects 60% in FY 2024,
40% in FY 2025
Discount rate 7%. The effect of
discounting for
FY 2024 is
considered to be
immaterial.
During the year ended 30 June 2024, the following occurred.
• In relation to the warranty provision of $656 004 at 30 June 2023, $420 000 was paid
out of the provision. Of the amount paid, $360 000 was for products with minor defects
and $60 000 was for products with major defects, all of which related to amounts that
had been expected to be paid in the 2024 financial year.
• In calculating its warranty provision for 30 June 2024, LMI made the following
adjustments to the assumptions used for products sold during FY 2024.
Estimated cost of repairs — products with minor defects $2 500 000
Estimated cost of repairs — products with major defects $6 000 000
Expected % of products sold during FY 2024 having no defects in FY 2025 80%
Expected % of products sold during FY 2024 having minor defects in FY 2025 17%
Expected % of products sold during FY 2024 having major defects in FY 2025 3%
Expected timing of settlement of warranty payments — those with minor defects All in FY 2025
Expected timing of settlement of warranty payments — those with major defects 50% in FY 2025,
50% in FY 2026
Discount rate No change. The
effect of
discounting for
FY 2025 is
considered to be
immaterial.
• The subsidiary of LMI, LSS Ltd, was in a strong financial position at 30 June 2024.
However, LSS was sued by one of its competitors for patent infringement in April 2024.
ACCT2110 Semester 2/2023
4

The compensation claimed in relation to the patent infringement is $87 million. The
hearing for the dispute had not been scheduled as at the date the financial statements for
2024 were authorised for issue. The legal adviser of LSS was of opinion that there was a
30% chance that LSS would be found guilty. If found guilty, there was a 60% chance
that LSS would need to pay $50 million as compensation to the plaintiff, and a 40%
chance it would have to pay $30 million compensation.
Required
(a) Calculate the warranty provision as at 30 June 2023. This should agree with the financial
statements provided in the question.
(b) Calculate the warranty provision for products sold during FY 2024 as at 30 June 2024.
(c) Determine whether the bank guarantee meets the definition of a provision or a contingent
liability for the year ended 30 June 2024 given the patent infringement action against LSS.
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CMP7000A CMP-7038B Math 263 LAW3016 CS371 STAT 334 FIN0008 ACC3004 STAT 371 ​COMP1921 MTH201 ACCT2000 UN3412 CIV6000 MATHS 3021 MATE7014 ECON1 CIBC6035 LAW121G COMM 321 CSC8204R TTM2033 CSCI 2600 MAE 115 LNG302 CENV6175W1 ECON30019 CPS2015 BST969 DDES9015 AMATH242 CS 1151 N1592 ACCT600 EG503G SMM519 EC318 Ecstatistics EEE 471 MARK2051 Topology COM00037H ACCT3000 MTHM501 EG501V COM00055H BUSN9085 GGR273 MATH 2B ITD102 MA214 ECON0060 ECE3114 ECMM447 Mechanics CCT361H5S BSAN3210 WELF2001 Fin3001 RESP5001 STA 137 Linguistics 101 CSCI368 CMPSC497 LUBS3655 OMBA 5355 BUSM2562 ​BFF5902 CYBR7001 CULT2005 ECON 7720 MTRX3760 FSE598 ​LUE1001 MGSC 7100 CS3240 COSC7500 ACCT3091 INFOGR TRAN 2080 DESIGN CIVE215001 CIVE2360 CPSC 8430 FNCE2003 Stoichiometry INFS6023 Quantitative Method Math 21D ECE5179 Design ​ECON8022 Chemical DMS 213 ADM1370 BFF5902 BFF2701 AGRI10051 AMN400 ECON7322 ​FINC5090 ​MATH1052 ​SciComp Elec4622 ​FINS5516 ENG 101 MMM143 CS431CA2 BSAN2201 EBSC7070 ES9v9-10 PLIN0009 DATA 8 MATH 101 BCPM0097 ​MAT 237 BISM2201 EEE8099 Physics 11 ECE2238B Biostat 234 ​ECON30009 INF10025 CHEM252 CCMA4008 CIVE 3007 STAT0031 ELEC ENG 3108 MGMT90140 CHEM 252 STAT3016 MMM095 ​MMGT6016 Legal STAT 311 ELEC9764 COMP 370 TCS 3053 EECS 1021 FIT1051 C/C++ EE3C COMP2003J COM398 COMP51915 Simulator FIN42330 8PRO102 PGD ELEC5160 XJCO1921 COMP5123M INFS 2042 CHE1148H ECA5313 IN3329 Microsoft Modeling B15 2TT COMP3687 COMP2432 DMS2030 KAN4TSF CFKG CSE 5322 CSE 445 STATS 3DA3 CHC5223 COMP1048 EL3105 EECS 3221 CS231 ME 4434 ITP4510 ITP4501 CSCI 5708 Controller EECE 5699 CPEN 231L CPN programs CSC8016 MATU9D2 ENGN4213 2. SVM. (10 points) Consider an SVM classifier using RBF kernel, and finish the following python code to search for the optimum kernel parameter γ. You are required to calculate the RBF function and search yourself, instead of using functions in Scikit-Learn (sklearn). def parameter search(gamma list ,Xtr,ytr,Xts,yts ,...): """ Parameters gamma list: A list of RBF kernel parameter gamma to search for Xtr: Training data, shape (ntr,nrow,ncol) ytr: Training labels, shape (ntr,) Xts: Test data, shape (nts,nrow,ncol) yts: Test labels, shape (nts,) ... Add other parameters as needed Returns: gamma optimum: The gamma with minimum error on Xts, yts """ ... return gamma optimum
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