Data is increasingly becoming an important factor in evaluating businesses and markets, especially when international investors set higher requirements for transparency. However, increased data volume also poses requirements for connectivity, standardization and information verification.
Talking to Lao Dong about this issue, Mr. Nguyen Minh Tu - General Director of CRIF D&B Vietnam - said that business data in Vietnam is still relatively fragmented. Besides the increasing amount of data, quality and cleanliness are issues that need to be improved.
According to Mr. Tu, when policies related to data exchanges, data processing and business are implemented, the volume of data will continue to increase. However, to serve investors, data needs to be standardized and better connected.
From the perspective of foreign investors, the groups of information of interest include legal data, including determining whether the enterprise actually exists and who is the final beneficiary; financial data and actual transactions of the enterprise. Notably, green capital flows and environmental, social and governance (ESG) requirements are increasingly being emphasized. According to Mr. Tu, data related to green capital and ESG in Vietnam is still lacking.
Another problem is that data sources have not been connected into a unified system. Investors can seek information from many management agencies, but the situation of data existing like "islands" makes it difficult to form a complete data ecosystem.
According to Mr. Tu, improvements need to be implemented from both the public and private sectors. Along with efforts to build national data infrastructure, the private sector can participate in the process of standardization, connection and improvement of data quality.
Data transparency is also directly related to capital mobilization capacity. In the context that Vietnam needs large resources for infrastructure development, especially loans and long-term capital, transparent information will help investors have a basis for risk assessment and strengthen confidence when participating in the market.
At the business level, Mr. Tu believes that it is not advisable to chase after owning as much data as possible. First of all, data must be related to actual operations and sufficiently reliable. Businesses can start "dataization" from daily operations, then supplement the necessary data sources before investing in analytical tools.
Data can also be used to warn early of risks. Customer and provider tracking needs to be done periodically instead of just evaluating when starting cooperation. Signs such as tax debt, social insurance debt, continuous changes in senior management personnel, or reduced order sources can provide signals about the partner's situation.
With artificial intelligence (AI), Mr. Tu emphasized that this is a decision-making support tool, not replacing humans. AI can process large amounts of data at high speeds, but the results depend on the quality of input data. Therefore, businesses still need experts to verify and evaluate before making decisions.
