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FREIGHT RECEIVABLES
12 Months Ended
Dec. 31, 2019
FREIGHT RECEIVABLES  
FREIGHT RECEIVABLES

NOTE 10 – FREIGHT RECEIVABLES

 

 

 

 

 

 

 

 

USDm

    

2019

    

2018

    

2017

Analysis as of 31 December of freight receivables:

 

  

 

  

 

  

Gross freight receivables:

 

  

 

  

 

  

Not yet due

 

39.8

 

44.0

 

25.5

Due < 30 days

 

22.5

 

18.8

 

26.0

Due between 30 and 180 days

 

25.3

 

20.5

 

18.4

Due > 180 days

 

6.0

 

4.4

 

2.7

Total gross

 

93.6

 

87.7

 

72.6

Allowance for expected credit loss

 

3.7

 

1.7

 

1.3

Total net

 

89.9

 

86.0

 

71.3

 

As of 31 December 2019, freight receivables included receivables at a value of USD 0.0m (2018: USD 0.0m 2017: USD 0.0m) that are individually determined to be impaired to a value of USD 0.0m (2018: USD 0.0m, 2017: USD 0.0m).

Management makes allowance for expected credit loss based on the simplified approach to provide for expected credit losses, which permits the use of the lifetime expected loss provision for all trade receivables. Expected credit loss for receivables overdue more than 180 days is 25%-100%, depending on category. Expected credit loss for receivables overdue more than one year is 100%.

Movements in provisions for impairment of freight receivables during the year are as follows:

 

 

 

 

 

 

 

 

USDm

    

2019

    

2018

    

2017

Allowance for expected credit loss

 

  

 

  

 

  

Balance as of 1 January

 

1.7

 

1.3

 

2.6

Adjustment to prior years

 

1.5

 

 —

 

 —

Provisions for the year

 

2.4

 

1.7

 

0.6

Provisions reversed during the year

 

(1.9)

 

(1.0)

 

(1.9)

Provisions utilized during the year

 

 —

 

(0.3)

 

 —

Balance as of 31 December

 

3.7

 

1.7

 

1.3

 

Allowance for expected credit loss of freight receivables have been recognized in the income statement under "Port expenses, bunkers and commissions".

Allowance for expected credit loss of freight receivables is calculated using an ageing factor as well as a specific customer knowledge and is based on a provision matrix on days past due.