【Financial Headlines】Data assets are "lived" and monetization methods need to be explored

At the beginning of May, all the staff of Shanghai Xinhua and Cloud Data Technology Co., Ltd. (hereinafter referred to as "Xinhua and Cloud") welcomed the "big event". The company obtained a credit of 1.5 million yuan from Bank of Shanghai in the form of data asset pledge. This is the first data asset pledge financing in the chemical industry. For Xinhua and Cloud, the significance of this "big event" is far greater than the credit itself. The company hopes to prove to the market that its data assets are valuable.

Data asset financing needs to go through the process of data asset ownership confirmation and registration, entry into the table (confirming data as an asset in the company's balance sheet), pledge, and evaluation. Compared with the common fixed asset financing, this is a new attempt.

Li Chuan, director of silicon and cloud operations, participated in the whole process. They first completed the on-site registration at the Shanghai Data Exchange (hereinafter referred to as the "Shanghai Data Exchange"), and then entered the data assets into the table. The enterprise hires an audit agency to audit the assets in the statements, and then conducts asset evaluation, so that third-party appraisal companies and banks can participate to complete the closed loop of pledge financing.

Looking at the whole country, in addition to the Shanghai Data Exchange, the Guangzhou Data Exchange, the Shenzhen Data Exchange, and some data trading platforms or trading centers are all providing similar access services.

Big data service science and technology enterprises such as Xinhua and cloud generally have the characteristics of "light assets and heavy data", and the key to monetizing data is to turn data into "assets". The data elements of an enterprise need to be analyzed by an authoritative institution, registered and confirmed by the asset management department, and evaluated to confirm their value before they can be turned into assets that can be pledged.

Li Chuan said that the data element market has not yet formed an official unified market, and there is currently a financing demand for data assets, but no third-party evaluation company's evaluation results can be generally recognized by the fund provider. Data assets have just been added to the table this year, and there are relatively few related cases, and it will take time to explore.

From the perspective of banking institutions, in the application of data assets, rights confirmation, valuation and compliance security have always been two major problems. Banks need to cooperate with professional valuation institutions to conduct a comprehensive assessment of the market value, uniqueness, and liquidity of data assets. A number of banking industry insiders believe that with the standardization and support of relevant policies, as the business model becomes more mature, more banks will join this innovative business, and data asset financing will achieve faster development.

Seek a compliant identity

As a big data research and application company focusing on the upstream and downstream industrial chain of the chemical industry, the current data products of Xinhua and Cloud cover enterprise data, warehousing and logistics data, price data and industrial chain data, etc., mainly providing industrial analysis services for local governments and chemical enterprises.

While serving local governments, Li Chuan found that due to the different natural resources, the characteristics of the chemical industry in different places are also different, and there may be missing parts in a certain link in the industrial chain. When local governments attract investment, they very much hope to complete the industrial chain (strengthen the chain and supplement the chain). When serving enterprises, Xinhua and Cloud have an industrial chain data product for chemical enterprises, and more business data of enterprises can be grasped through algorithm models, such as which chemical enterprises are operating and selling products, and whether the products have procurement needs.

In July 2022, the Cyberspace Administration of China imposed a huge fine of 8.026 billion yuan on Didi, sounding the alarm for the data industry. The management of Innosilicon and Cloud is deeply aware of the importance of data compliance. However, as an enterprise, there are certain limitations to researching whether data is compliant or not on your own. Therefore, they thought of the Shanghai Data Exchange. The agency was established in November 2021. For enterprises, the Shanghai Data Exchange is like a guiding unit, pointing out the direction for data enterprises on how to operate their business more safely and compliantly.

In 2022, Xinhua and Cloud will start to register on the Shanghai Data Exchange. In Li Chuan's view, the difficulty of registration lies in the process of confirming data rights. The company is required to provide proof related to the data, such as proof of data holding, proof of lawful data collection. If the data is sourced, the company also needs to provide relevant contracts, etc.

Li Chuan told the Economic Observer that if a company wants to monetize a certain data, it must have the right to hold or operate the data. Confirmation is a challenge because data businesses have been in business for a decade or two before the relevant regulations were introduced, and few people knew the source of every piece of data before, and it was difficult for companies to ensure that all their data was fully compliant.

The relevant person in charge of the Shanghai Data Exchange told the Economic Observer that enterprises need to pass the review and confirmation of a complete set of rights confirmation rules and systems of the Data Exchange, and the Data Exchange will also introduce law firms and other relevant data service providers.

Li Chuan said that law firms will identify the company's data products from various latitudes and confirm the integrity of the relevant evidence chain before issuing a compliance assessment report for the enterprise.

The entire data right confirmation lasted for one to two months, and Xinhua and Cloud passed the assessment and completed the registration work. After Xinhua and Cloud settle in the Shanghai Data Exchange, their data products can be listed. After listing, the data of Xinhua and cloud can enter the field, which is equivalent to having a "property right certificate". The data business is more compliant, making the enterprise operation more "secure".

After the registration was completed, the Xinhua and cloud teams were thinking about how to truly reflect the value of technology as a technology company. The R&D investment of Chiphua and Cloud is accounted for in the "expenditure" account in the company's balance sheet, but this does not objectively reflect the value that the technical team brings to the enterprise.

In August 2023, the Ministry of Finance issued the Interim Provisions on the Accounting Treatment of Enterprise Data Resources (the "Interim Provisions"). When the management of Silicon and Cloud learned the relevant policies, they found that the inclusion of data assets in the table can reflect the true value and business contribution of the technical team in the financial statements.

On January 1, 2024, the "Interim Provisions" came into effect, and Xinhua and Cloud began to carry out the work of entering data assets into the table and hired audit institutions to audit data assets.

According to the reporter's understanding, at present, the assets entered into the statement according to accounting standards are based on the cost method. According to the product attributes of Xinhua and Cloud, the cost invested by the enterprise in the R&D process includes manpower, technical servers, data resources, etc., which are included in the "intangible assets" account of the balance sheet in the form of costs.

According to the above-mentioned relevant person in charge of the Shanghai Data Exchange, according to the "Interim Provisions", after enterprises sort out their own data resources and include them in their accounting statements, they can become asset packages traded on the Shanghai Data Exchange.

From asset valuation to financing

After the assets are entered into the statement, if the enterprise has a need for pledge financing, the Shanghai Data Exchange will cooperate with a third-party appraisal agency to evaluate the asset value of the enterprise based on the data assets of the enterprise in the table, based on the transaction data of the enterprises on the exchange. The relevant person in charge of the Shanghai Data Exchange said that because the appraisal agency cannot obtain the data of market transactions, in the process of data asset valuation, most appraisal agencies use the income method, that is, to evaluate the value of data assets by estimating the income they bring.

According to Li Chuan, the evaluation mainly looks at the economic value brought by the data, that is, whether the data can be monetized. Whether it is a data product developed or a data report written, through a certain calculation, it is proved that it can be monetized on a legal basis, and these data can become useful data assets, otherwise they are "junk data" lying in the database.

The relevant person in charge of the Shanghai Data Exchange said that the uniqueness and growth potential of data assets will also be considered when assessing, and the company's own rules and regulations and the advanced degree of data asset management will also be considered.

Soon after the completion of the entry form, Xinhua and Cloud decided to participate in the evaluation and financing at the Shanghai Data Exchange. Li Chuan said that for Xinhua and Cloud, the original intention of the pledged loan is to prove the value of the company's data assets, so as to gain market recognition and play an exemplary role for big data enterprises in the chemical industry. As for the amount of financing, Xinhua and Cloud don't care too much.

Xinhua and Cloud participated in the evaluation this time, and the whole process took more than a month. During this period, the company held several meetings with the Shanghai Data Exchange and the Bank of Shanghai, and continued to run in. Li Chuan remembers that they would throw out an idea, but the bank would have its own considerations. After all, data assets are different from traditional fixed assets, and banks need to pay attention to the current value of the product and the profit margin that can be realized in the future, and also need to ensure the security of the pledged assets, so as to lend to the enterprise. As the lead unit, the Shanghai Data Exchange will also coordinate in the process of evaluation and introduce a third-party evaluation company to participate in the evaluation.

Whether it is the Shanghai Data Exchange or a third-party appraisal company, there will be a complete set of evaluation models and processes, but how to be adopted and accepted by different banks, in Li Chuan's view, these need to be run-in. Banks will have their own internal appraisal system, and according to the appraisal report issued by a third-party appraisal agency, they will raise their own questions about certain points in the report, and it is not possible to determine the loan amount completely according to the assessment of the asset value by the third-party appraisal company. Corporates, banks, and third-party valuation firms need to sort out these doubts gradually, a process that takes a lot of time.

"Data assets and fixed assets are two different assets, and the evaluation of data assets lacks sufficient case support in the industry, so institutions will be more cautious in the evaluation process and will pick out a lot of details, so the entire evaluation process takes longer than the evaluation of fixed assets." Li Chuan said.

According to the Economic Observer, through the formation, confirmation, and valuation of data assets by the Shanghai Data Exchange, the model that helps revitalize enterprise data assets is called "Digital Easy Loan". At present, 7 cases of "Digital Easy Loan" have been implemented, and the main partners are not only Bank of Shanghai, but also China Construction Bank and Agricultural Bank of China.

The significance of pattern exploration

In addition to the registration and appraisal services provided by the exchange, third-party appraisal companies in the market can also provide the services of title registration, appraisal and report issuance. An appraisal staff member of Beijing Zhongjinhao Asset Appraisal Company (hereinafter referred to as "Zhongjinhao Asset Appraisal") told the Economic Observer that enterprises need to complete the data inventory and data assets in the table before evaluating data assets. They can provide businesses with some methods for data inventory and tables. After the company's data assets are confirmed, they will grant the company a certificate of compliance and then conduct an asset evaluation.

The above-mentioned staff said that when enterprises do data inventory, they should sort out according to the type of data assets, and confirm whether the data can be classified into data assets, and it is best to sort out the data assets with realizable value for subsequent evaluation.

According to the Economic Observer, under the joint promotion of Zhongjin Hao Asset Appraisal, the Chengdu Branch of Industrial Bank issued the first data asset pledge loan in Sichuan Province on March 27 this year, providing a loan of 5 million yuan for enterprises.

Some banks have begun to try to use their data assets as collateral to provide financing services for enterprises. From the end of 2023, IB will begin to explore financial products and services based on data assets. In April 2023, China Everbright Bank Shenzhen Branch cooperated with Shenzhen Data Exchange to successfully land the country's first data asset financing business for small and micro enterprises.

Enterprises, evaluation agencies, data exchanges and banks have explored the path of data element capitalization, which has made data assets "live".

The digital economy has become the core driving force for economic growth in recent years, and the digitalization process has profoundly affected the financial industry. With the in-depth development of a new round of scientific and technological revolution and industrial transformation, the wave of digitalization is booming, and the status of data as a basic strategic resource and key production factor of the country has become increasingly prominent.

The relevant person in charge of Ping An Bank told the Economic Observer that financial institutions attach great importance to the value of data assets and regard them as their core competitiveness. The assetization of data elements in the financial industry can effectively promote the multi-scenario application and multi-subject reuse of data, cultivate new products and services based on data elements, realize knowledge diffusion and value multiplication, and promote the innovation of data asset financial services.

Dong Ximiao, chief researcher of Zhaolian, said that the exploration of data asset pledge financing model is of positive significance. For technology-based enterprises that have a large amount of data but lack traditional collateral such as plant and equipment, these explorations can solve the problem of financing needs but lack of qualified collateral. For some large and medium-sized enterprises with both fixed assets and intangible assets, this model enriches the collateral of the enterprise and makes it more convenient for them to carry out financing.

Relevant people of IB also believe that as China's data element market enters the fast lane of development, all parts of the country are actively exploring new models of financing using data assets, showing the huge potential of data asset financialization. Under the regulation and support of relevant policies, data asset financing will achieve rapid development.

More unanswered questions

The capitalization of data elements in China is still in the early stage of development, and the valuation of data assets, the use of security and compliance, risk control, and post-loan risk disposal are still being explored.

The Economic Observer learned from the interview that financial institutions generally feel that the direction is clear and the funds are sufficient, but the grasp is not enough. Due to cost and capacity constraints, some small and medium-sized banks are still relatively backward in their basic digital capabilities, and need low-cost and efficient third-party platforms to promote the digital transformation of the entire industry. In addition, the complexity of data asset categories makes the valuation of data assets more complicated, and banks need to cooperate with professional valuation institutions to conduct a comprehensive assessment of the market value, uniqueness, and liquidity of data assets.

The above-mentioned Ping An Bank person believes that the valuation of data assets and the safe and compliant use are still the two major problems that hinder the application of data assets. Due to the intangibility, complexity and technical dependence of data assets, it is of great significance to build an appropriate data asset value evaluation system and establish a clear data ownership system to accelerate the wide application of data assets. At the same time, data assets should be used well and managed, and how to use data assets safely and effectively is also a major topic worth exploring.

How to check the risk of data assets is another issue worthy of attention. The Economic Observer learned from the Shanghai Data Exchange that the Shanghai Data Exchange is currently able to rely on on-site data and regularly use the market method to evaluate the value of enterprises' data assets and provide risk warnings for banks. The market method is a data asset valuation method based on market conditions, which evaluates the value of the same or similar data assets by comparing and analyzing their recent or historical transaction prices.

A person from the Shenzhen branch of Everbright Bank told the Economic Observer that the value of data assets is highly volatile, and it is difficult to monitor prices in real time and warn of price drop risks in loans.

IB personnel believe that to do a good job in data asset risk management, we should mainly pay attention to the operating conditions of borrowing enterprises, changes in the value of data assets, and changes in the market environment. In addition, the market liquidity of data assets determines the ease of monetization of data assets. In the future, the monetization of data assets needs to be further explored.

The relevant person in charge of Ping An Bank said that from the bank's point of view, through regular risk assessment of data assets, potential security threats and vulnerabilities can be identified. In addition, banks can continue to invest in the latest data protection and management technologies, such as artificial intelligence, machine learning, etc., to improve data security and processing efficiency. In addition, data related risks can be reduced by updating systems and software in stages, taking advantage of the latest security features and patching security vulnerabilities, continuously conducting data asset assessment and technology updates, and effectively managing and protecting data assets.

Risk control of digital assets is an important consideration for banks when doing this business. What should I do if a data asset financing loan is at risk? In Dong Ximiao's view, this is a new topic, and it is necessary to solve the problems of how to price, transfer, and circulate data assets. If the number of business cases gradually increases, new requirements will be put forward for the transfer and circulation of data markets, including improving the infrastructure construction of data assets, establishing a platform for transaction transfer and circulation, and introducing relevant systems and supporting measures, such as building a unified national data trading market (exchange), otherwise it will be difficult for data assets to exert their true value.

"At present, the construction of the data element market is still in the early stage of cultivation, and there is no standard model and reference case for how to dispose of data assets." The above-mentioned person from the Shenzhen branch of China Everbright Bank suggested that at the legal level, it is necessary to formulate special laws and regulations to clarify the rules for the ownership registration and transaction flow of data assets. In terms of supervision, it is necessary to formulate management systems such as market access, risk management and control, and information disclosure to prevent ethical and operational risks. With the improvement of relevant work and supporting measures, data assets have the conditions for large-scale financial utilization.