News Detail

Wuhu's Public Resource Trading Platform Issues Invoices Instantly on Payment

On September 1, Wuhu's public resource trading data-sharing platform launched an instant invoicing function: once a winning bidder pays, the system automatically issues a digital electronic invoice and pushes it to the recipient, the first such case in the province. The Jiangbei emerging industry cluster tax bureau had previously built a direct link with the tax administration's Leqi platform for the operator, enabling automatic invoicing for computing power, batch transaction settlement and smart ledger collection. In one week of operation, average daily invoiced value reached 140,000 yuan and manual invoicing workload fell by nearly 92 percent.

Industry News国家税务总局安徽省税务局Source
2026-09-21

Wuhu has moved invoicing into its public resource trading platform. On September 1 the city's public resource trading data-sharing platform launched instant invoicing: as soon as a winning bidder pays, the system automatically issues a digital electronic invoice and pushes it out, the first case of its kind in Anhui. The Jiangbei emerging industry cluster tax bureau had already built a customised direct connection to the tax administration's Leqi platform for the platform operator, enabling automatic invoicing for computing power, batch settlement and smart ledgers; the upgraded scheme now extends to public resource trading with unified standards on invoice recipients, types and delivery. Manual filing, online declaration and back-office verification are no longer needed, sharply cutting time and labour costs for companies and easing the platform's verification burden. In its first week the platform invoiced an average of 140,000 yuan a day and cut manual invoicing work by nearly 92 percent. The company's finance head said the smart invoicing model has been proven and can serve as a replicable template for its computing power, data operation and digital trading platforms. Tax authorities said they will keep expanding smart tax applications to more big-data scenarios.