Why Isolated Bank Scoring Fails to Prevent Counterparty Default: OSINT Case Study of a Scam Deal

A social entrepreneur operating as an individual entrepreneur (IE) signed a contract in October 2023 for the supply of complex IT equipment worth more than 600,000 rubles, of which 500,000 rubles came from a targeted state grant. The agreement required 100 percent prepayment.

Before transferring the funds, the entrepreneur checked the supplier, conditionally named AvtoTransSnab-90 LLC, through the compliance service of a major bank. The system assigned the counterparty a green marker indicating high reliability. The transaction was approved and payment was sent.

The supplier shipped goods worth only 15,000 rubles as cover, then ceased performance and effectively vanished. While the entrepreneur pursued court proceedings and attempted debt recovery through bailiffs, the Department of Investment Policy demanded return of the grant due to failure to achieve performance targets. To keep the business running, the entrepreneur had to purchase the remaining equipment at personal expense for another 485,000 rubles and repay the grant funds. The net loss for the micro-business reached almost one million rubles. Bailiffs and arbitration courts yielded no results in recovering unjust enrichment.

Four Critical Red Flags Missed by Automated Compliance

The bank algorithm evaluated the company in isolation and at a single point in time. On the query date, AvtoTransSnab-90 LLC was active, had no recent lawsuits, and no open enforcement proceedings. The robot checked formal checklists and approved the deal. Human analysis of the same public data immediately identified stop factors.

• Industry mismatch: The name and primary OKVED code in EGRUL clearly indicated cargo transportation, yet the contract concerned IT equipment supply. A sudden change in operational profile without adding relevant activity codes is a classic risk marker.
• Absence of financial reporting: The state information resource for accounting statements (GIR BO) showed the organization had not filed balance sheets for the three years preceding the transaction. Combined with a minimal charter capital of 10,000 rubles, this pointed to a typical dormant shell company.
• Direct affiliation via FTS registry: The Transparent Business service revealed that a 49 percent co-owner of the supplier was also the 100 percent owner of Computer Campaign LLC, registered at the same address. The second company was an actual IT wholesaler.
• Financial distress of the linked entity: At the time of the deal, Computer Campaign LLC was effectively bankrupt, with tax debts exceeding one million rubles, arbitration claims over five million rubles, and negative net assets of 248,000 rubles.

The beneficial owner had redirected incoming client payments to the clean transport entity to avoid imminent account seizures on the profile IT company.

Two years later, AvtoTransSnab-90 LLC was liquidated by tax authorities as an inactive entity and the debt was written off. The sister IT company was declared bankrupt under a simplified procedure for an absent debtor with budget liabilities exceeding seven million rubles. The beneficial owner was added to the FTS blacklist and disqualified for three years.

The core vulnerability of commercial bank scoring remains its single-entity approach. Automated systems assess a legal entity in a vacuum and ignore the collapse of related businesses owned by the same beneficiary. Basic manual checks against official state databases continue to outperform closed bank compliance algorithms.