Checking account controls change from now on also because tax authorities can cross many different data.
Here are the alarm bells that will make the Finance and Revenue Agency suspicious.
The government wants to raise money and will do so with very insightful investigations. The tax man will from now on use special algorithms based on artificial intelligence to cross Current account, credit card and ISEE. Anything that does not match between these three data sources will immediately start investigations. Let’s see how. Numerous rumors arose about how the tax levies moved to cover the discrepancies between what Italians declared and what they really earned or possessed. The tax authorities’ algorithms will generate two datasets, which are two large lists of names Which tax taxes will be monitored with special attention.
Lists: Analysis and Monitoring
The first list is called The “analysis” and those who end up in it will be monitored as they are considered to be at risk of evasion. Obviously, whoever is on this list has put some suspicious behavior into the algorithms. The second list will be called ‘Control’ and for those who end up in this data set, things are certainly more dangerous, given that the tax authorities consider them to be at high risk. Investigations will begin immediately. Among other things, these data sets will be kept for 10 years, and whoever ends up on these lists will surely be sifted with special interest. The main tool for finding tax evaders becomes just that The popular ISEE model that many Italian families diligently assembled.
Pay attention to the ISEE model
The ISEE model crossed with accounts and credit card transactions can instantly blow the revenue agency fly because the inconsistencies become immediately apparent. The so-called savings meter is another strategic component of the agency as it monitors the progress of various accounts and movements, moment by moment which are made on it can provide for taxes practically in real time the cross-section of what is not returned between what has been declared and what has actually been conveyed.
Let’s see the behaviors that get the attention of revenue. Sudden peak spending or, conversely, long periods without withdrawal. Constant and regular movements that seem to find no comfort in income. The AI is programmed to detect any anomalies and send the call sign to the dataset.
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