Tinkoff has developed a machine learning-based model that can detect fraud in the confirmation phase of a loan application. He said so in a statement.
According to Oleg Zamiralov, deputy director of the Tinkoff Center for Ecosystem Security, the technology makes it possible to suppress more than 90% of cash loan applications processed under the influence of social engineering.
The company has reinforced the scoring, which it previously used to verify the solvency of a client, with signs and parameters that indicate possible fraud. Among these signs: sociodemographic factors, anomalies in the application itself, which are often used to receive instructions from scammers, etc.
To develop a fraud detection model, Tinkoff analyzed several million requests, including those that customers submit under the influence of social engineering.
The pilot has been tested since late last year.
Author:
Anastasia Marina
Source: RB
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