The Wheat from the Chaff #4

From the recent episodes that have occurred in the country, much has been said about Governance and Compliance, two closely related subjects. Many of our readers have been asking in recent weeks how data can help in these areas and related processes. I start with the direct answer: a lot!

As part of my job, every week I read a lot of content about data, technology, and artificial intelligence (also known as AI). I filter them and send you the best ones, every Sunday.

Hello everyone 👋 ,

From the recent episodes that have occurred in the country, much has been said about Governance and Compliance, two closely related subjects. Many of our readers have been asking in recent weeks how data can help in these areas and related processes. I start with the direct answer: a lot!

It is time to separate the wheat from the chaff…

Image from Shutterstock.com

Less is More

There are public data that, with proper consent to comply with the General Data Protection Law (GDPL), can be correlated and generate valuable insights for decision-making.

Sometimes, companies are created for fraudulent purposes, such as the so-called "shell companies." These companies are illegitimately established and registered, and they do not engage in any actual activities; they only exist on paper and are criminally used to issue invoices and document the movement of goods from other companies.

In this context, data can help identify corporate structures with a low probability of occurrence. For example, Company X has two partners, A and B. Partner A is a career professional in a large corporation, while Partner B was a professional truck driver three years ago and is now a partner in six holding companies. This fictional example illustrates how data can be helpful. However, it's important to note a few details:

Historical data needed to be considered; if I had relied solely on the current data (partner in six holding companies), I would not have noticed the abrupt change in Partner B's behavior over time.

Knowing where to find the information, some of the data in the example can be found in the Annual Social Information Report (ASIR) and the General Registry of Employees and Unemployed Persons (GREUP): mandatory information that companies must provide.

But, Jhon, can this be used in our everyday lives? The example still seems distant to me. I agree with the challenge, and I will use an example from my experience in recent days. To provide context, data from Serasa Experian shows that between January and September 2022, Brazil recorded over 3,046,294 attempts of consumer fraud, one every 8 seconds.

I really wanted to buy a ticket to watch a game at Rio Open - the largest tennis tournament in South America - with my wife, but the tickets were already sold out. So, we searched on social media and found people who had bought tickets but supposedly wouldn't attend and were willing to sell them.

We looked for the best prices and asked for a photo of the ticket. The photo contained the buyer's name and Social Security, and for the seller, we asked for her Pix (Brazilian instant payment system, similar to Zelle and Venmo) information so that we could make the supposed payment. With these two pieces of information, we initiated investigations.

Using the buyer's Social Security, we found the full name (matching the name on the ticket), residence address, demographic data, and professional information. When simulating the transfer using Pix, we were able to discover the seller's full name. From there, we managed to locate her data, such as Social Security, demographic information, and professional details.

What is the probability of the buyer and the seller knowing each other? Very low! To summarize the long story, the buyer resides in Belém do Pará, is an entrepreneur in the vehicle industry. On the other hand, the seller lives in Campo Grande, Rio de Janeiro, is 58 years old, and has no records of professional activity. The profile picture on the seller's WhatsApp and social media did not correspond to the age recorded in the Internal Revenue Service.

Interesting topics Brazil:

  • 🔗 Link: 30 careers that can go to the next level with AI

  • 🔗 Link: How AI can prevent some natural disasters

Trending topics Global:

  • 🔗 Link: Don’t get scammed! ChatGPT scams are spreading through social media

Guest of the Week: Rafael Nadal

Taking advantage of the context of the Trend is to be Simple text of the week, I searched for some interesting phrases from people who inspire me and came across this one from Nadal, which I believe fits well to start the week:

"Doubts are not overcome; you always live with them. What can be done is to give your best every day and strive to do things better each day."

See you Sunday…

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