When Innovation Becomes "Hard Currency": How Should Enterprises Calculate Their Accounts?

At an artificial intelligence research institute in Sichuan Province, several uniquely designed robotic dogs are shuttling back and forth in the testing area—some crawling into simulated pipes to perform dredging operations, others raising mechanical arms to inspect corrosive environments. On another workbench, an AI large model doll has just finished debugging; soon, it will interact and converse with visitors.

But this company, which seems to be “holding the future,” only has enough funds in the bank to cover this month’s expenses. Without a factory, equipment, or collateral, the brains of a dozen engineers are the company’s entire assets.

Holding technology and orders, yet blocked outside due to lack of collateral, when innovation itself becomes the most valuable asset, how can financial services keep up?

Today, this solution has been incorporated into national strategy.

When “Reading Reports” Meets “Building the Future”

The “14th Five-Year Plan” emphasizes “accelerating high-level technological self-reliance and strength,” explicitly calling for “strengthening original innovation and tackling key core technologies.” This year, the government work report further proposed to “enhance full-chain and full-lifecycle financial services for technological innovation,” establishing a regular “green channel” mechanism for financing in key core technology sectors.

Why set up a dedicated “green channel”?

Industry experts say that tech finance focuses not on ordinary technology but on technologies closely linked to high-level self-reliance and essential for developing new productive forces. This means that frontier areas with strategic value require a different financial service logic from traditional models.

Data shows that by the end of Q4 2025, there are 275,000 technology-based small and medium-sized enterprises (SMEs) nationwide supported by loans, with a loan approval rate of 50.2%. This means nearly half of tech SMEs are still excluded from traditional credit due to lack of collateral or cash flow support.

The Sichuan AI tech company is a microcosm of this “other half.” Its team masters core pipeline robot technology, deeply engaged in the corrosive environment dredging robot industry, and has cooperated with large state-owned enterprises for years. However, these “soft strengths” are difficult to quantify as credit under traditional credit assessment models.

“From looking at cash flow to evaluating technology” sounds simple, but implementing it requires a whole new evaluation language.

Machines That Are “Understood”

In September 2025, Hong Hui, a consultant from Ping An Rongyi, visited the company. Instead of focusing on fixed assets on the report, she spent three days “reading” the enterprise: founder background, technological patents, order stability, industry prospects. These factors once considered “soft information” were broken down, quantified, and assessed one by one.

Eventually, the company was matched with a no-collateral microfinance product, and 915,000 yuan was quickly disbursed. After the Spring Festival in 2026, the company’s leader said, “This money came just in time.”

More than one machine dog has been “understood.” In Hefei, Anhui Province, a company specializing in AI rubber defect detection reduced manual inspection error rates from 15% to 0.3% with its self-developed defect detection system. At the end of 2025, a delayed accounts receivable caused a brief funding gap.

In Chongqing Jiangjin Shuangfu International Agricultural Trade City, a fruit wholesaler wanted to expand pineapple procurement from Vietnam but was stuck on orchard deposits. A consulting agent used the “Xingyun 2.0” AI smart loan system to approve 400,000 yuan on the spot, completing the entire process without leaving the market.

These seemingly scattered cases point in the same direction: financial services are shifting from “collateral worship” to “value discovery.” Those previously unaccounted “soft strengths”—technological barriers, founder backgrounds, order stability—are becoming new credit anchors.

Let Technology Understand Technology

A continuous service methodology is enabling more stories like these. To date, Ping An’s “Prism” project has delivered over 380 million yuan of “financial lifeblood” to key local industries.

Let data speak, solving evaluation challenges. The “People + Enterprise” intelligent risk control model incorporates founder backgrounds, technological patents, and order flows into assessment dimensions, turning invisible innovative value into quantifiable credit assets.

Industry experts believe that the core of tech finance lies in building a comprehensive financial service system covering the entire cycle of technological innovation, breaking down barriers between innovation chains, industrial chains, and capital chains, and fostering mutual nourishment and collaborative progress. To achieve this, financial institutions must learn to “read” technology with technology and serve innovation with innovation.

From robotic dogs to Hefei’s AI laboratories and Chongqing’s fruit stalls, these seemingly distant scenes are connected by the same service logic: making “light assets” no longer a barrier to financing for tech startups, and turning innovation itself into the most substantial credit credential.

At the start of the “14th Five-Year” new journey, such stories are happening in more and more places. The robotic dogs are still shuttling in the testing area, and the AI doll is about to enter scenic spots to interact with visitors. Zhang Yongsheng has already begun planning the next round of R&D.