Datarisk, a company specializing in artificial intelligence solutions, has launched an indicator that identifies customers with a higher propensity to gamble, to be used in analyzing the risk of default. The Brazil Gambling Probability Score uses registration data from both the individual and their relatives, as well as recent activity history (frequency and number of different bets), to determine the chance of them placing bets in the next three months.
Carlos Relvas, head of data science at Datarisk, reports that when there is a relative who gambles, the probability of the person also becoming one increases by 77%. The increase is even greater, at 216%, in cases where the parents are gamblers.
"During the tests carried out with the product, we identified a high incidence of people who started gambling after a close relative made a similar move", explains Rivas.
The tool also cross-references data such as clients' presumed income, gender, and age. Gambling is more common among men (70.8%) and the average age is 34 years, but almost half of the gamblers (47.8%) are between 25 and 40 years old.
The score also revealed that 63.9% of gamblers are employed with a formal contract and have an average salary of 4.7 minimum wages
“Our goal is to enable companies to make more assertive decisions and mitigate potential payment difficulties”, explains Relvas.
All these indicators along with other factors make up the score. "In the end, we assign a score ranging from zero to a thousand, where a thousand indicates the highest propensity to become a gambler, and zero, the lowest", adds Carlos Relvas.
The Datarisk Gambling Probability Score can be integrated quickly and efficiently into the platforms of contracting companies through an API, ensuring agility in implementation.
Datarisk was founded in 2017 with an angel investment. The following year it was accelerated by Visa and named one of the 100 most innovative startups in Latin America. In its latest funding round, in 2021, the company raised $2 million.
Source: GMB
