On the Eve of Financing: The Suspicion of "Brush Orders" Behind Monthly Sales of 12 Million Yuan

In 2021, a cross-border e-commerce platform focusing on the European and American markets was at a critical juncture of development. After years of intensive cultivation, the platform's monthly sales exceeded 12 million yuan. Relying on a stable supply chain and precise product selection strategy, it has accumulated a good reputation among young European and American consumer groups. The Series A financing progress was smooth, and the investors had drawn up the Term Sheet, pending the completion of the final due diligence before signing and remitting the payment.

However, a due diligence report pushed everything to the brink. The third-party institution entrusted by the investors found that:

• Suspicion of Related Transactions: 15% of the platform's orders come from 3 affiliated operation agencies
• Abnormal Order Behavior: Some orders have the phenomenon of "repeated orders placed from the same IP address in a short period of time"
• Suspicious Logistics Information: The logistics information of some orders is inconsistent with the receiving address

The conclusion pointed directly to the core: "Suspected brush orders, the authenticity of data is questionable". If this conclusion is established, the platform will not only lose this round of financing, but also may miss all subsequent capital opportunities due to the collapse of business reputation. More fatally, the rent for overseas warehouses in the next quarter is about to be paid, and the capital chain is on the verge of breaking.

Emergency Intervention: Triple Verification in 48 Hours to Clarify Doubts with Data

Upon receiving the enterprise's request for help, the special team of our firm quickly assembled and established the core strategy of "speaking with data" - no argument, no excuse, and responding to every doubt with original data and cross-validation results.

Data Extraction: Penetrating Verification of 3,000 Orders

Within 48 hours, the team completed the extraction of original data of 3,000 orders from the platform in the past 3 months, and established a triple verification system of "IP address traceability + payment flow cross-validation + logistics track tracking":

First Layer: IP Address Traceability

Comparing the matching degree between the IP address of the order and the physical location of the receiving place. The results showed that 87% of the orders initially marked as "abnormal" had a reasonable correlation between their IP addresses and the receiving locations (such as commercial IPs and school IPs near the receiving locations), and were thus excluded.

Second Layer: Payment Flow Cross-validation

Verifying the associated information between the payment account and the bank card under the recipient's name. It was found that only 3.2% of the orders had the suspicion of "payment on behalf" - further tracing showed that most of them were international students buying goods on behalf of their family members in China, which is a normal consumption behavior and does not constitute malicious brush orders.

Third Layer: Logistics Track Tracking

Conducting a full-process tracking of the logistics tracks of the remaining suspicious orders, and comparing the differences in collection time, transit nodes, signing records with normal orders. The results showed no systematic abnormalities.

After the triple verification, the so-called suspicion of "brush orders" was clarified one by one: the platform data is true, and there is no malicious brush order behavior.

Communication with Investors: Rebuilding Trust with Verification Report

Clarifying the facts is only the first step; rebuilding investors' trust is the real challenge. The team sorted out the verification process and methodology into a detailed "Data Authenticity Verification Report", including:

• Explanation of Verification Methodology
• Screenshots of Original Data Samples
• Demonstration of Cross-validation Process
• Itemized Explanation of Abnormal Orders
• Final Conclusion and Confirmation of Data Authenticity

With this report, the team accompanied the enterprise founder to hold multiple communication meetings with investors, responding to their core concerns one by one. In the end, the investors recognized the verification results and agreed to proceed with the financing at the original valuation.

Risk Control Innovation: Dynamic Bet Adjustment Mechanism

Although the doubts were clarified, investors still had concerns about the authenticity of subsequent data. To completely dispel their worries, the team innovatively designed a "dynamic bet adjustment mechanism", linking the valuation with the subsequent data performance:

• Core Indicator: Proportion of real orders (the proportion after excluding all abnormal orders)
• Assessment Cycle: Monthly monitoring within 6 months after financing
• Trigger Condition: If the proportion of real orders is lower than 90% for 3 consecutive months
• Adjustment Mechanism: Valuation is automatically reduced by 15%

This mechanism controls the investor's risk exposure within an acceptable range, and at the same time forces the platform to continuously strengthen data compliance management.

System Upgrade: Dual-wheel Drive of Merchant Management and Data Compliance

While the financing was landed, the team assisted the platform in building a long-term compliance mechanism at the institutional level:

Revision of "Merchant Management Rules"

Adding the clause of "immediate delisting + confiscation of margin for brush orders", clearly stipulating:

• Identification criteria and verification procedures for brush order behavior
• Delisting process and margin handling rules

• The notary office shall conduct full-process evidence preservation for the rule publicity process to ensure procedural compliance and evidence fixation

Data Compliance Clause in "Shareholder Agreement"

Adding a special "Data Compliance Representation and Warranty" clause to the investment agreement:

• The founder team shall bear joint and several liability for the authenticity of historical transaction data
• If the investor suffers losses due to data fraud, compensation shall be paid twice the investment amount
• Deeply binding the founder's personal liability with data authenticity

Fund Utilization: 60% for the Construction of AI Anti-fraud System

After the 20 million yuan financing was in place, the platform invested 60% of it (about 12 million yuan) in the construction of an AI anti-fraud system:

• Real-time Monitoring: Conduct real-time multi-dimensional scoring (IP, payment, logistics, etc.) for each order
• Abnormal Early Warning: Automatically mark and push to manual review when abnormal rules are triggered
• Rule Iteration: Continuously optimize the anti-fraud model based on newly added data

Results Achieved: 98% Compliant Orders, Successfully Listed on the NEEQ

With the dual support of systems and technologies, the platform's data quality has been significantly improved:

• **The proportion of compliant orders increased to 98% in 2021**, far exceeding the industry average
• Successfully listed on the NEEQ (National Equities Exchange and Quotations), becoming a benchmark case in the field of data compliance among listed enterprises in the same period
• Included in the reference sample of local cross-border e-commerce compliance guidelines, with significantly improved regulatory recognition