Of virtual informers and others

Interesting initiative

A very interesting initiative recently used in Panama City is called the “tweeting pothole“: A television channel has placed sensors in potholes in the city streets, which are struck whenever a vehicle falls into one of the potholes. The sensor, which has the sign “#” in blue, clearly identified with the hashtags of Twitter and painted with the color of the social network, triggers the publication of a message that reminds the authorities, not only than a pothole in the city has not been fixed, but also that a vehicle has just fallen into it.

Increasingly, I am convinced that more and more devices will be connected to the Internet, using sensors for all types of measurements. I want to share with you a couple of experiences that were presented in the last week of April, at the 18th technical conference of CeATS, (Sub-National Tax Administrations Center) which dealt with the use of technology as a support for the tax control, among others.

  • The administration of the Mendoza Province, host of the event, presented us its brand-new “drone” that fly over areas of the city, taking pictures to identify improvements in buildings, compare them and verify whether they were declared or not. It is easy to imagine that, beyond the complexities of recognition and image processing, geographic references, and the determination of differences between what is seen and what was declared, only the simple press release about the drone presence raises the feeling of subjective risk associated with taxpayers who are tempted to omit declaring an improvement. When they will see the “bug” flying, many will wonder: Is this device a bird, a plane, or the drone of the administration?
  • A somewhat similar strategy was developed by the administration of the city of Buenos Aires: They hired a photography service to scan the buildings of the city and identify new buildings, looking for those non-declared.
  • The administration of the province of Buenos Aires has created its own version of what we sometimes called a fixed point: the presence of a representative of the Administration in a business to ‘tell‘ the number of clients. They also check the cash registry during one or more days, to see if the operations coincide with the movement of an average day. Electronic counters of clients have been placed at the entrances of restaurants, recording the number of entries and exits of persons in certain moments. The electronic counter registry can discount the amount of people who reasonably go in and out without being clients; it may serve to have an indication of the volume of people entering a venue.

If the tax administration has all the electronic documents that support operations, it would be possible to determine the corresponding taxes from the reported operations.

All the operations are reported or when some operations, particularly those carried out in cash with end consumers, are made without documenting transactions. In these cases, it would be possible by using, for example, the input product matrix or by comparison with reported purchases and sales of other similar businesses of similar size, to identify ranges of probability of non-compliance and amounts associated to a possible difference between the stated amount and the real economic activity. These can be detected through elements such as the amount of beverages purchased from soft drinks and sodas distributors, the quantity of ingredients purchased at wholesale chains, or the kilowatt-hours consumed in certain periods. However, on the one hand, not all tax administrations have access to electronic invoices or their adoption level is still low, and on the other hand, some economic activities are more risky with regard to the practice of not using invoices. The possibility of having objective values that allow determining elements of the tax base, or to obtain evidence to estimate the risk is very interesting.

Those sensors and counters can be very accurate indicators of the economic activity, such as measuring the production of drinks or passage of cars, trucks and motorcycles on a highway concession counter. On other occasions, they can only provide indications of the moments of highest activity. For example counting people in restaurants that can be compared with the accounting records. They could determine whether the records of the restaurant in terms of amounts and schedules correspond in volume with the days and times detected by cameras and therefore detect that there was omission of registration of several sales operations but without determining the exact amount of consumption. By the way, signs of economic activity also could be obtained from photographs (including the selfies) of social networks services users.

Of course, moving to the automation and massive use of presumptive determination methods will never be easy. It will need a large set of efforts that will include the identification of points where you can get data, the creation of specific algorithms that refine and analyze the data, to determine the crosses, generate regressions and statistical inference rules that identify the risks. Of course, the cost benefit analysis to make these developments is essential; this is not about creating a solution for a nonexistent problem and these options should only be used to attack/address serious attitudes of non-compliance.

Greetings.

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