At the recent Ningbo Science and Technology Week, local technology companies presented a wide range of cutting-edge innovations. Yet behind the rapid emergence of new technologies lies a persistent challenge: how can the real technological value and growth potential of these companies be accurately assessed?
To address this issue, a research team led by Professor Hua Xiuping from University of Nottingham Ningbo China (UNNC) has developed an “AI and Big Data-based Multi-dimensional Holographic Profiling Technology for Technology Enterprises”. The system acts like a “CT scan” and “genetic test” for companies, helping financial institutions and government agencies better identify the innovation capabilities and future potential of technology enterprises.
From financial metrics to innovation capability
Traditional financing assessments often rely on collateral and stable cash flow, making it difficult for knowledge-intensive technology companies to demonstrate their true value. To overcome this limitation, Professor Hua’s team analysed data from nearly 30,000 enterprises and established an innovation-focused evaluation framework that goes beyond conventional financial indicators.
Using machine learning and AI large language models, the system analyses factors such as R&D investment, innovation quality, growth performance and commercialisation capability. It can also interpret patents and technical documents to assess the maturity and future prospects of technologies, transforming complex technical information into accessible insights for decision-makers.
“For some start-up teams, they may not yet be profitable, but they could possess cutting-edge core technologies or even be pioneers in niche sectors,” said Professor Hua. “Under traditional banking scoring systems, such companies may receive relatively low ratings, but within our evaluation framework they may achieve much higher scores.”
Supporting regional innovation and industrial development
The system also incorporates policy priorities and local industrial needs, enabling it to identify technologies that can address practical challenges and contribute to regional development.
Since 2013, the technology has supported local government initiatives and has been applied in Ningbo’s innovation capability evaluation system for technology enterprises, as well as in generating “white lists” for credit support policies. To date, it has served more than 10 financial institutions and over 2,900 enterprises, facilitating approximately RMB 47 billion in credit support for companies in strategic emerging industries and future-oriented sectors.
“This system helps governments identify promising technology enterprises at an earlier stage, while also supporting companies in securing external financing,” Professor Hua noted. “It enables more targeted allocation of science and technology finance resources, helping to create a positive cycle linking technology, capital and industry.”