Bayesian Networks on Income Tax Audit Selection - A Case Study of Brazilian Tax Administration
نویسندگان
چکیده
Tax administrations in most countries have more corporate and personal information than any other government office. Data mining techniques can be used in many different problems due to the large amount of tax returns received every year. In the present work we show an essay of the Brazilian Tax Administration on using Bayesian networks to predict taxpayers behavior based on historical analysis of income tax compliance. More specifically, we tried to improve a previous risk based audit selection which detects a large amount of taxpayers as high risk. However, in its current form it identifies much more cases than the tax auditors can handle. Our first results are promising, considerably improving tax audit performance.
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