

Economics and Business
Quarterly Reviews
ISSN 2775-9237 (Online)







Published: 15 March 2025
Demographic and Socioeconomic Determinants Use of Financial Products/Service
Wilson Rajagukguk, Omas Bulan Samosir, Josia Rajagukguk, Hasiana Emanuela Rajagukguk, Perak Samosir, Ruth Nattassha Napitupulu
Universitas Kristen Indonesia, Universitas Indonesia, Institut Teknologi Indonesia, Universitas Bunda Mulia

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10.31014/aior.1992.08.01.653
Pages: 115-121
Keywords: Financial Product/Service, Susenas 2023, Demographic And Socioeconomic Factors, Binary Logistic, Indonesia
Abstract
The use of financial products/services in Indonesia is growing. And is one of the factors of economic growth. This study aims to investigate the demographic and socio-economic factors that influence the use of financial products/services. The data used are based on the 2023 National Socio-Economic Survey. The object of analysis is the population aged 15 years and over who use at least one financial product/service. There were 241,075,975 respondents in this study, of which 23.17% used at least one financial product/service. The dependent variable is the use of financial products/services. The independent variables used are Gender, Education, Island of residence, Urban/rural, and Marital status. The analysis was carried out using bivariate and multivariate methods. Multivariate analysis using a binary logistic regression model was used in the analysis. The results showed that higher use of financial products/services was associated with being male, college graduates, living in Java, living in urban areas, and being married.
1. Introduction
Recent research has provided strong evidence that financial development has a significant positive impact on economic growth (Papaioannou (2007), Ross Levine (2005), King and Levine (1993), Levine and Renelt (1992), Sala-i-Martin (1997), Ciccone and Jarocinski (2006). Financial development is related to economic growth even in industrial countries (Thiel (2001). A number of studies have also found the impact of financial inclusion or financial products on welfare (Chipunza, K. J., & Fanta, A. B. (2023), Campbell, J. Y. (2006), Munyegera, G. K., & Matsumoto, T. (2016), Hidayat, P., & Sari, R. L. (2022). Nanziri, E. L. (2016)). Not only on economic growth, financial products/services are positively associated with the welfare of a household and a country. Thus, financial products/services are important and need to be studied. From the perspective of neoclassical growth theory, economic growth is driven by the accumulation of factor inputs and technical progress, with a potential role for finance in particular in assisting in capital accumulation. The endogenous growth approach emphasizes the role of entrepreneurship and innovation, allowing some leeway for finance to direct incentives toward research and innovation or rent-seeking. In this sense we can say that a developed financial system in a country is beneficial to growth. Sutton, C. N., & Jenkins, B. (2007). show that countries with well-established, efficient and well-used financial systems have lower poverty rates and better economic growth. Several studies have concluded that financial sector deepening contributes to poverty reduction (Beck et al. (2007), Jalilian & Kirkpatrick (2005), Quartey (2005)). Policy implications directed at developing a national strategic plan aimed at increasing access to finance combined with policies to improve the level of governance to maximize the impact of financial access on economic growth (Emara, N., & El Said, A. (2021).

Figure 1. Percentage of formal financial services usage by Country Group, 2024
Source: World Bank, World Development Indicators. 2025. Own calculation
From Figure 1, it can be seen that the higher the use/utilization of financial services is associated with the level of economic development of a group of countries. High-income, upper-middle-income, middle-income, lower-middle-income, and low-income countries are respectively 96.365, 84.33%, 72.37%, 62.28%, and 38.99%). While at the world level, the use of formal financial institutions is 76.2%.

Figure 2. Account ownership at a financial institution (% of population ages 15+) with
GDP growth (annual %), countries in the world. 2021
Source: World Bank, World Development Indicators. 2025. Own calculation
Figure 2 shows that every 1% increase in account ownership at a financial institution or with a mobile-money-service provider (% of population ages 15+) is associated with a 0.0078% increase in GDP Growth (%) across a number of countries in the world.

Figure 3: Account ownership at a financial institution (% of population ages 15+) with GDP per capita (US$) of countries in the world. 2021
Source: World Bank, World Development Indicators. 2025. Own calculation
Figure 3 shows that every 1% increase in Account ownership at a financial institution is associated with an increase in GDP per capita of US$ 540.85. From Figure 1, Figure 2, and Figure 3 it can be seen that at the global level, financial institutions are positively associated with economic growth and welfare. Boakye & Amankwah (n.d) conducted a study using interview data from 3643 citizens on the determinants of financial product usage in Ghana. It was found that financial literacy, income, income or expenditure stability, urban residence, access to income, access to communication channels, and local residents' perceptions of the inherent benefits of a product, as factors that determine whether someone will use a financial product. It was also found that financial literacy, financial products that accommodate unstable cash flows, communication about the inherent benefits obtained from financial products, and the use of mobile phones and the internet to provide services will increase the acceptance of financial products in Ghana.
Furthermore, the study wanted to conduct a study on the determinants of financial institution usage in Indonesia using data from the 2023 National Economic Survey. Susenas 2023 provides data on various aspects of economic levels and fulfillment of life needs such as clothing, food, shelter, income, security and employment opportunities. Susilowati, E. & Leonnard, L. (2019), found that in Indonesia there is a significant positive relationship between individual characteristics (gender, age, income level, age, employment sector) on the use of financial services, financial service inclusion, motivation to use financial services, and credit sources. Kumar, S., Pradhan, K.C. (2024) conducted research in South Asia on the determinants of financial product/service use. It was found that individuals who are male, older, richer, and more educated tend to have access to financial product services, it was also found that income and have a greater influence.
2. Data and Analysis Methods
2.1. Data
The data in this study uses/is taken from the 2023 National Socio-Economic Survey (SUSENAS). The 2023 National Socio-Economic Survey (Susenas) is a survey conducted by the Central Statistics Agency (BPS) to collect economic data. Data obtained from Susenas are used for national-level planning and evaluation. SUSENAS 2023 was implemented by the Central Statistics Agency in March and September and covers all provinces in Indonesia. SUSENAS 2023 is implemented to meet the need for data and economy at the district, provincial, and national levels, including data on the achievement of Sustainable Development goals. The sample of the March 2023 National Socio-Economic Survey (Susenas) is 345,000 households. This sample is used to produce statistical data at the national, district, and city levels. The 2023 SUSENAS data is cross-sectional data.
Table 1: Percentage distribution of using financial products/services aged 15 years and above by background characteristic
Background | Number of observation | Percentage |
Gender | ||
Male | 121,448,272 | 23.77 |
Female | 119,627,703 | 22.57 |
Education | ||
Don’t have a diploma | 48,290,664 | 7.78 |
Elementary School Equivalent | 59,797,855 | 13.65 |
Junior High School Equivalent | 47,979,851 | 20.23 |
Senior High School | 63,631,935 | 34.81 |
College | 21,375,670 | 56.53 |
Island | ||
Sumatera | 53,578,834 | 20.33 |
Jawa | 136,014,459 | 24.77 |
Bali and Nusa Tenggara | 13,289,436 | 22.86 |
Kalimantan | 14,785,780 | 22.86 |
Sulawesi | 17,498,199 | 22.28 |
Maluku and Papua | 5,909,266 | 16.27 |
Urban/Rural | ||
Urban | 14,1986,849 | 27.55 |
Rural | 99,089,126 | 16.90 |
Marital Status | ||
Married | 132,333,151 | 27.85 |
Unmarried | 92,074,775 | 16.98 |
Divorced Living | 4,026,992 | 25.83 |
Divorced Dead | 12,641,058 | 18.51 |
Total | 241,075,975 | 23.17 |
Source: SUSENAS 2023. Own calculation