Debt Ageing / Late Payment Prediction by Dusan Korcak | Jun 2, 2021 | 0 comments Welcome to your Debt Ageing / Late Payment Prediction. Keep in mind that you have only 2 attempts! All topics in certification are available in our knowledge base Name: Email: 1. Debt ageing algorithm is in other words: Supplier late payment prediction algorithm. Customer late payment prediction algorithm. Supplier goods late arrival algorithm. 2. Debt ageing algorithm is providing user with following results High, medium and low probability of late payment Percentage probability Late payment status 0 or 1 All of the above 3. DSO (days sales outstanding) means: Average number of days that it takes a company to collect payment for a sale. Average number of days that it takes a company to make a payment to supplier. 4. iERP Debt ageing algorithm can help to reducing days sales outstanding (DSO) usually by five days what can reduce trapped cash by: 5% 30% 60% 5. Debt ageing Trainer Sources is used for upload of how many data files? Two; customers and invoices Three; customers, invoices, and locations Four; customers, invoices, payments and locations 6. If there is no integration to customer ERP, SQL scripts should be mapped within customer database True False 7. Columns tab in training section is used to: Training execution Validation of data load to the system API setup 8. Is possible to print PDF report with data validation on Trainer Columns screen? Yes No 9. How many types of validation is source file processing in Debt ageing algorithm performing? 3 6 8 10. If error is found in the data on Trainer Columns screen, you can correct errors by: Uploading new file on Trainer sources screen. Correcting data in CSV file and then click on Reload and validate button User has to create a new project 11. Data tab on Trainer screen is used to: Review loaded data Reload data in case user finds any error in the data All of the above 12. What is recommended ration between testing and training parameters to be set on Invoice file in Data tab of ‘Trainer’ section? 80% / 20% ratio 50% / 50% ratio 60% / 40% ratio 13. Does user need to perform any configuration before machine learning execution on Training tab in ‘Trainer’ section? Yes, there are many settings parameters No, it is straightforward process 14. What kind of training complexities can user set on Training tab in ‘Trainer’ section? Fast training complexity only. Precise training complexity only. User can choose between Fast or Precise training complexity. 15. When user should be using Fast training complexity? If they want to validate the whole debt ageing workflow without need to wait for precise training to be completed. If they want to get more precise results of Debt ageing algorithm. 16. Machine learning training can occupy your CPU to 100% while performing training of algorithms: True False 17. Duration of algorithm training is dependent on: Dataset size Computer configuration Dataset size and Computer configuration 18. Sources tab on Forecaster section is used for: Upload the most recent data to be used for most accurate predictions based on already trained model. Machine learning training. Review forecasting results. 19. Visualisation on Data tab on ‘Forecaster’ section consist of BI data displaying: Outstanding AR receivables only. All AR receivables. Customers with highest debt. All of the above. 20. Debt ageing forecasting results can be reviewed: Directly in iERP Studio. Exported as CSV. Integrated with API. All of the above. Time is Up! Time's up Submit a CommentYour email address will not be published. Required fields are marked *Comment * Name Email Website
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