Current status of risks of granting green credit to Vietnamese enterprises
According to statistics from the State Bank of Vietnam, green credit expectations in the banking system have grown by an average of 22,2%/year in the period of 2017-2023, notably, green credit growth has surpassed the average credit growth rate.
By the end of 2024, 50 credit institutions (CIs) have recorded green credit balance, mainly focusing on the fields of renewable energy, clean energy, and clean agriculture. These figures show that green credit is becoming a credit trend at Vietnam credit institutions. To achieve these results, credit institutions have proactively integrated environmental and social factors into their development strategies and operating models.
With the orientation of sustainable development, green projects are increasingly attracting attention. Green capital attracts the attention of businesses with incentives on interest rates and lending time. However, if the disbursement of green capital flows is not transparent and accurate, it will pose many potential risks to credit institutions.
Credit risks: Coming from a lack of financial and non-financial information. In reality, businesses often pay little attention to publishing information about non-financial targets. Many green enterprises do not have transparent financial reports, or have not proven the financial efficiency of green projects. Some businesses have applied unprecedented new green technologies for assessment, adding that revenue from green projects is often slow and depends heavily on management policies.
Environmental risks: Measuring whether projects are truly green when granting credit is a challenge for credit institutions when there are no clear standards.
Legal risks: With an unfinished legal framework for green credit, banks and credit institutions will have difficulty determining the boundary between green projects and regular projects. Also because of the lack of comprehensiveness of policies, green credit institutions may face risks when policies change, affecting the feasibility of green projects.
Information risk: Greenwashing is a term that refers to businesses that deliberately turn their projects into green projects to access green capital flows. While banks and credit institutions find it difficult to verify the transparency and accuracy of environmental reports.
The green credit data ecosystem has not been fully developed and synchronized
The green credit data ecosystem was born to limit risks to green credit activities, providing a transparent and effective green capital flow.
Green credit data ecosystem is a financial system that promotes sustainability and environmental protection by encouraging green investment projects. Green credit data ecosystem an ecosystem of multidimensional linkages between financial institutions, businesses, management agencies, and data technology.
In particular, credit institutions will provide credit, evaluate green loan applications and provide transparent data to make investment decisions. The enterprise will provide data on green projects, environmental data such as CO2, renewable energy, etc. The state management agency will play a role in issuing policies and supervising green credit flows to ensure sustainable development goals. In the context of high technology, this ecosystem will apply high technologies such as AI, Blockchain, IoT to increase transparency and efficiency.
The green credit data ecosystem will not only help credit institutions reduce risks in granting credit through accurately identifying green projects, helping to automate and standardize credit appraisal processes, increase credit performance and reduce risks. This ecosystem also helps countries integrate into the global green financial market, businesses participating in the ecosystem will have the opportunity to easily access international capital sources to invest in green projects.
In China, green credit is integrated into the national credit system and requires financial institutions to periodically report green financial data. The data will include green loans, renewable energy projects and carbon emission standards as well as environmental violation records. With the participation of NHTW, the Ministry of Ecology and Environment, the national credit information center, China's green credit data ecosystem is clearly demonstrating its supporting role in creating transparent and effective green capital flows.
In the ASEAN region, Singapore is a pioneer in green credit. Singapore's Green Credit Industry Taskforce (GFIT) is an ecosystem of large commercial banks, insurance companies, investors, consulting companies, research organizations and management agencies. GFIT has built a system of standards for classifying green financial activities for the Asia region, publishing ESG data for businesses, developing a Greenprint platform to collect and process, and share ESG data from many sources. Thanks to that, Singapore easily standardizes the assessment of green credit, providing data for the green credit appraisal process.
The green credit data ecosystem in Vietnam is not yet fully developed and synchronous. Although Vietnam has had policies to develop green credit since 2015, and has also recognized the role of green credit in the green economic transformation process, factors such as data infrastructure and legal framework are still incomplete.
Vietnam currently lacks a complete and synchronous legal framework and regulations on the classification of green projects. Banks and credit institutions have not agreed on a common standard when determining the green factor of projects offered by enterprises. This leads to a lack of synchronization in granting green credit to credit institutions and banks, causing risks of creating green projects to benefit from interest rate incentives.
Vietnamese enterprises are now starting to manage and report on environmental data. Although there are specific regulations related to the disclosure of information on sustainable development in annual reports, many businesses have not yet fully and fully published data. The data is still disjointed and mainly owned by businesses and TCTDs, so it is difficult to verify the accuracy. And we currently do not have any reputable data assessment and authentication agency operating in the market. Therefore, the current green data is lacking in quantity and has not been verified for reliability in quality.
Data analysis personnel are still lacking, many credit institutions do not have enough technology as well as personnel with appropriate capacity and knowledge to analyze and process environmental data.
It can be seen that the demand for green credit in Vietnam is increasing, however, green loans are still segmented and it is difficult to assess the transparency and efficiency of these loans due to the lack of an ESG data system. Most Vietnamese enterprises are small and medium-sized, with weak capacity to manage environmental issues and publish information on sustainable development, so access to green capital is limited.
In addition, although there are regulations for the green bond market and guidelines for green credit activities, Vietnam does not have a data platform connecting parties (management agencies, credit institutions and enterprises). Therefore, building a green credit data ecosystem is necessary if Vietnam wants to develop a green financial market, where green capital is used effectively.
Solutions to build a green credit data ecosystem
Some proposals to deploy the Green Financial Data Ecosystem model in Vietnam in the coming time. To build a Green Credit Data Ecosystem, we need to build 4 main pillars, including: national database on green credit, Green project identification standards (taxonomy), data collection and processing technology, coordination between credit institutions of management agencies and enterprises.
Therefore, I propose some solutions to focus on developing these 4 pillars as follows:
We can learn from Singapore's GFIT model or China's data model when integrating environmental data into credit records. From there, it is possible to build a national database on green credit.
Develop a system of Green project identification standards (Taxonomy) from the lessons of China and Singapore.
China's Green Taxonomy was initiated in 2015 by the People's Bank of China (PBoC), initially as standards for green bonds, then expanding to green credit and sustainable investments. Green classification levels are also changed over time, based on emission standards to classify the green conversion levels of projects.
Singapore Asia Taxonomy has been developed by GFIT since 2021, with the goal of building a standard classification set of green projects suitable for Asia conditions. Singapore's Taxonomy is integrated with the ESG Greenprint data platform and can automatically track and report movements of green capital flows. Singapore is implementing a green transformation model to help all industries have a transformation roadmap.
Applying digital technology in data collection and processing to ensure timeliness and efficiency
Build a green credit data ecosystem with the participation of parties, including businesses and governments, foreign investors and organizations, when participating, having the opportunity to access diverse and accurate data systems. In particular, management agencies including the Government, the Ministry of Finance and the State Bank need to issue more detailed policies and instructions for green credit. Quickly standardize green project classification standards to limit risks related to project appraisal and green credit granting to businesses.
In addition, credit institutions also need to increase personnel training and improve knowledge of green project appraisal officers, ensuring that appraisal activities before granting green capital are correct and accurate.
