The Ministry of Finance is working to improve its use of data to create more detailed profiles of Thai citizens, encompassing both liabilities and assets, in order to support economic development.
The creation of a “data lake” will enable the government to design better national development policies and identify the strengths and weaknesses of each area of the country, according to permanent secretary Lavaron Sangsnit.
The system will aggregate various types of information about people nationwide, including tax records, credit bureau information, land ownership, utility payment history and loan data. This information will be valuable for formulating future policies, such as the so-called negative income tax that would more effectively target welfare payments, he said.
Mr Lavaron said the data would also reflect each individual’s financial discipline, which would be beneficial for financial institutions when considering loan approvals.
A ministry source who requested anonymity said the data lake would include information on individuals, legal entities and spatial data, utilising inputs from 20 different sources for analysis.
Examples include: income data from taxes collected by the Revenue, Customs and Excise departments; state welfare card data for 13.5 million individuals from the finance ministry; welfare data from the Comptroller-General’s Department; savings deposit information for 45 million people from the Deposit Protection Agency; National Credit Bureau data for 32 million people; student information from the education ministry; information on 24.5 million social security insured persons from the Social Security Office; data on 90,000 Otop (one-tambon one-product) entrepreneurs and 180,000 products; data on 175,000 lottery vendors from the Government Lottery Office; and information on 342,000 public drivers’ licences from the Department of Land Transport.
This data will help identify the strengths and weaknesses of each area in the country in various aspects, including infrastructure, public health, education, economic stability, human resource challenges and the environment. For example, for infrastructure alone, there are 12 indicators such as night-time light intensity per area and road length per area.
In education, there are 15 indicators such as English proficiency and the number of schools per area. In terms of human resource challenges, there are 21 indicators including population density, mortality and suicide rates.
In the past, the Fiscal Policy Office used data to drive key government policies in seven projects such as the state welfare card project for 13.5 million people, and the “Eat, Shop, Spend” (Chim Shop Chai) project with 11.8 million participants.