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Nour-Baklouti/Tunisian_Fraud_Detection_Challenge

Domaine:

socioeconomic

Type de record:

datasetproject
Créateur:
Nou
Hôte:
Detect tax fraud using the Ministry of Finance of Tunisia's data # Tunisian_Fraud_Detection_Challenge Detect tax fraud using the Ministry of Finance of Tunisia's data Tax fraud is the intentional act of lying on a tax return form with the intent to lower one’s tax liability. Under-reporting is one of the most common types of tax frauds. It consists of filing a tax return form with a lesser tax base. As a result of this act, fiscal revenues are reduced, undermining public investment in much-needed services. The objective of the challenge is to detect tax fraud. This is one of the main priorities of local tax authorities which are required to develop cost-efficient strategies to tackle this problem. Using historical data, a supervised machine learning technique that detects potential fraudulent taxpayers will increase the operational efficiency of the tax supervision process. Evaluation The evaluation metric for this challenge is Root Mean Square Error. Challenge Link : zindi.africa

Visit

github.com

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