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How AI aids in identifying fraudulent companies.

The list of domestic manufacturers prioritized in government procurement has decreased from 6,000 to nearly 2,000.
How AI aids in identifying fraudulent companies.

Artificial intelligence has assisted the Ministry of Industry and Construction in identifying fraudulent enterprises. This was reported by the head of the department, Kanat Sharalpaev, during an on-site government meeting, as conveyed by a correspondent from the business information center Kapital.kz.

“Thanks to the electronic database, we have the capability to analyze this information in a very short time. We have 2070 companies here – that amounts to millions of lines of data. For instance, electronic invoices, and this analysis can be conducted by artificial intelligence in just minutes. This is the first significant advantage. The second capability of this system is to identify anomalies,” he noted.

The minister clarified that artificial intelligence can help detect discrepancies in the volume of produced goods, raw material purchases, electricity consumption, number of employees, and the pension contributions made for them.

“In this system, we can easily distinguish between fake producers and genuine local enterprises that truly manufacture products. The third element we are utilizing: at the beginning of this year, we prioritized local producers in government procurement. This is an exemption from the national regime. Currently, there are 2070 enterprises in the database, starting from over 6000 enterprises. Thanks to the identified anomalies, we cleaned the data and ended up with those enterprises that are indeed local producers, which will receive support measures, and the government will make efforts to further engage them,” emphasized Kanat Sharalpaev.

The minister specified that the exemption from the national regime covered 4,000 product groups. With the help of AI, it is evident which industries are benefiting the most from this measure, and which are benefiting less.

“This allows us to quickly, in real-time, address errors,” Kanat Sharalpaev clarified.