The Social Insurance Institution (ZUS) Is Knocking on Doors and Checking Contracts. 20,500 Inspections Have Already Been Carried Out, with 90% of Them Finding Irregularities.
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The Social Insurance Institution (ZUS) conducts inspections less frequently, but detects irregularities in 9 out of 10 cases. It has challenged over PLN 11 million in the region. Find out which industries are under scrutiny. Read: Nearly 90% of inspections result in fines. ZUS makes predictions with incredible precision on the Spotted Lublin - Lublin News website.
The Social Insurance Institution (ZUS) has just published the latest data on business inspections, and the numbers are impressive. From January to August 2026, inspectors conducted 20,529 inspections of contribution payers. Irregularities were found in 18,495 cases, or 90.1% of the inspected entities. The financial impact of the ZUS's activities amounted to PLN 373.3 million. At the same time, ZUS admits that today it conducts inspections differ…
ZUS reported that the detected irregularities often concern the overlap of social security entitlements, underestimation of the contribution calculation base, incorrect settlement of persons working for their own employer and the use of various forms of employment to reduce the contribution burden.
From January to August 2026, ZUS employees conducted 20,500 inspections of companies. Irregularities were identified in over 90 percent of cases. This statistic is the result of data analysis and the selection of entities for inspection at the highest risk of violating regulations.
Over 90 percent of ZUS inspections result in the detection of irregularities. This high effectiveness has a specific reason – companies are not chosen at random. The Institution identifies practices related to employment and contribution settlement that particularly attract inspectors' attention.<br /><br />
From January to August 2026, ZUS employees conducted 20,500 inspections of companies. Irregularities were identified in over 90% of cases. This statistic is the result of data analysis and the selection of entities for inspection at the highest risk of violating regulations.
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