2025 Namibia Financial Inclusion Survey
Namibia, 2025
Get MicrodataIdentification
NAM-NSA-NFIS-2025-v01
2025 Namibia Financial Inclusion Survey
2025 NFIS
| Name | Country code |
|---|---|
| Namibia | NAM |
Other Household Survey [hh/oth]
Namibia Financial Inclusion Survey
The 2025 Namibia Financial Inclusion Survey (NFIS) was conducted by the Namibia Statistics Agency (NSA) in collaboration with the Bank of Namibia (BoN), the Financial Literacy Initiative (FLI), and technical support from FinMark Trust. Building on four previous iterations (2004, 2007, 2011, and 2017), the study’s primary purpose was to generate nationally representative baseline indicators on the levels of access to, and usage of, formal and informal financial services across Namibia's adult population. The study was executed to establish an empirical foundation to guide key policy frameworks, including the Namibia Financial Sector Transformation Strategy (NFSTS 2025–2035), regulatory reforms, and private-sector product design. Utilizing a probability-based, three-stage stratified cluster sampling design based on the 2023 Population and Housing Census frame. Fieldwork was conducted between October and November 2025 via Computer- Assisted Personal Interviewing (CAPI). The realized sample of 1,863 households across all 14 administrative regions achieved a 95.1% response rate, representing a weighted national adult population of 1,818,168 individuals.
A defining methodological characteristic of the 2025 NFIS is its expanded target population, which lowered the inclusion threshold to individuals aged 15 years and older to capture early financial behaviours, mobile money adoption, and informal savings habits as youth approach formal financial eligibility. Analytically, the study applies standard FinMark Trust Access Strands spanning financial access, savings, credit, insurance, and remittances to rank primary service usage hierarchically and remove product overlaps. The 2025 round also uniquely incorporated emerging development themes, evaluating domestic solar energy adoption, consumer demand for renewable energy financing, and green finance mechanisms in agriculture. Through these frameworks, the Principal Investigators sought to address critical questions regarding the proportion of the population that is financially served versus excluded, how access has evolved across demographic and urban-rural divides since 2017, the specific economic, structural, or psychological barriers impeding financial adoption, and the role of digital infrastructure and identity documentation in deepening financial participation.
The primary subject areas investigated include household demographics, lived poverty, income streams, financial capability, and sector-specific financial engagement. Key demographic and socio-economic variables comprise age, sex, educational attainment, urban/rural residence, region, personal monthly income, Lived Poverty Index scores, and possession of essential identification documents. Financial inclusion variables capture overall status across the Access Strand (banked, formal non- bank, informal only, or excluded). Sectoral variables measure account ownership, preferred channels (ATMs, bank branches, cellphone banking, point-of-sale, mobile wallets), transaction frequencies, safekeeping options, savings mechanisms, credit sources, loan application outcomes, debt attitudes, insurance holdings, risk mitigation strategies, and remittance channels and frequencies. Finally, livelihood and energy variables examine primary income sources, farming classification (subsistence vs. commercial), input financing, and domestic solar system adoption drivers and barriers.
sample survey data[ssd]
Individual adult aged 15 years or older residing in a selected private household for at least six months; the household is a complementary unit for socio-economic indicators.
Version
NAM_NSA_2025_NFIS V1
2026-09-25
Scope
Household Demographics, Farming Activities, Income and Expenditure, Access to Infrastructure, Financial Capability, Savings, Borrowing, Risk and Mitigation, Remittances, Bank Penetration, and Informal Financial Products.
Coverage
The 2025 Namibia Financial Inclusion Survey (NFIS) achieved comprehensive nationwide geographical coverage by surveying private households across all 14 administrative regions of Namibia. Built upon the 2023 Population and Housing Census frame, the survey's multi-stage sampling design utilized 196 Primary Sampling Units (PSUs) distributed across 107 urban and 89 rural clusters to capture local and regional population dynamics. While fieldwork was executed across the entire country to ensure extensive spatial dispersion, the sampling scheme was tailored specifically to produce robust, statistically representative estimates at the overall national level and across urban and rural domain splits.
The universe (or target population) of the 2025 Namibia Financial Inclusion Survey (NFIS) comprises non-institutionalized individuals aged 15 years and older residing in private households across all 14 administrative regions of Namibia, spanning both urban and rural areas. To be defined as a member of this target population, an individual must have resided in the selected household for at least six months prior to enumeration and be available and physically and mentally capable of completing the interview. The universe explicitly excludes institutionalized populations living in collective quarters—such as student hostels, old-age homes, hospitals, prisons, and military barracks—though private households situated within institutional compounds (such as teachers' quarters) are included. In total, this study universe represents an estimated weighted population of 1,818,168 eligible adults living across 755,292 private households nationwide.
Producers and sponsors
| Name | Affiliation |
|---|---|
| Namibia Statistics Agency (NSA) | Government of the Republic of Namibia |
| Name | Abbreviation | Role |
|---|---|---|
| FinMark Trust | FMT | Technical assistance |
| Name | Abbreviation | Role |
|---|---|---|
| Namibia Statistics Agency | NSA | Funding |
| Bank of Namibia | BON | Funding |
| Financial Literacy Initiative | FLI | Funding |
| Name | Affiliation | Role |
|---|---|---|
| Field Staffs | Namibia Statistics Agency | Data Collection |
| General Public | Namibia | Respondents |
Sampling
A three-stage sample design was used in this survey, which is based on a stratified design with probability proportional to size selection of Primary Sampling Units (PSUs) at the first stage and sampling of households with systematic sampling at the second stage.
In the second stage, households were chosen from the selected PSUs. After all households in a PSUs were listed using a Tablet, ten (10) households were randomly selected using a systematic sampling algorithm built directly into the Computer Assisted Personal Interviewing (CAPI) application, to enhance the sampling process. The sample was designed to provide accurate national and urban/rural estimates, using 1 960 households across 196 Primary Sampling Units of which ten (10) households were selected in each PSU. To improve the precision of key indicators for the study, the design prioritized increasing the number of Primary Sampling Units (PSUs) while reducing the household count per cluster (from 14 to 10). This shift toward many small clusters rather than a few large ones enhances geographical dispersion and minimizes intra- cluster correlation, resulting in more robust sample coverage and improved estimation efficiency.
The third stage of the sampling process was the selection of an individual who is 15 years or older, to be interviewed by each of the selected households. The individuals were those available during the duration of the survey and were mentally, and physically capable of being interviewed and had resided in the selected household for at least the last six months. This process began with listing all the household members who are 15 years or older in each selected household using the tablet. The Kish Grid sampling algorithm was an integral component of the CAPI application, to eliminate selection bias when choosing a single respondent from a multi-person household for a survey.
95.1% overall household response rate (1,863 out of 1,960 expected households successfully interviewed). Rural response (96.0%) was slightly higher than urban (94.3%).
Weighting is a process of accounting for the selection probabilities and non-response in a sample survey. The sample weights were constructed to account for the following: the original selection probabilities (design weights), non-response, weight trimming, and benchmarking to known population estimates from the latest 2023 PHC. The sampling weights for the data collected from the sampled households were constructed so that the responses could be properly expanded to represent the entire target population of Namibia. The inverse sampling rate (ISR) of this selection probabilities adjusted for non-response is called the design (base) weights, which are assigned to each of the households.
Given the population figures based on the 2023 PHC, weight adjustment of the design weight was undertaken to ensure that the calculated survey estimates conform to the population totals. However, due to the limitations of post-stratified weight adjustment in controlling a large number of cells at different levels, a complex procedure known as weight calibration was instead applied.
Survey instrument
Structured into modules: A (Demographics), B (Farming), C (Income/Expenditure), D (Access to Infrastructure), E (Financial Capability), F (Savings), G (Borrowing), H (Risk), I (Remittances), J (Bank Penetration), K (Informal Products), L (General).
Primary data cleaning
The CSPro application was used for structural and completeness checks, to ensure that all PSUs were included in the raw data, all questionnaires had appropriate final response codes, all persons and households allocated unique identifiers, etc. The Python software was used to examine data for structural inconsistencies and duplicates.
Secondary data cleaning
Stata v17 was used for robust verification of variables, ensuring that all responses were withing the expected value ranges and no skipping and consistency checks were violated. Additionally, checks were done on open-ended questions such as Other"s (specify) to determine if they could be coded to pre-determined categories or left under Other.
Missing values were also assigned accordingly;
.a For single response variables: Not applicable, observation outside universe
.b Across multiple response variables: All categories missing but observation within universe (legitimate missing)
.z For multiple response variables: Observation within universe but not stated (legitimate missing)
New variables were also derived as per the tabulation report (such as grouping age, grouping income, creation on binary financial inclusion variables, etc)
The dataset follows the order of the questionnaire. The variables in the dataset are labelled orderly according to the questionnaire. Specifically, the alphabetical order is applied in naming variables, following the order of sections, questions and categories. All derived variables are at the end of the data file.
Data collection
| Start | End |
|---|---|
| 2025-10-06 | 2025-11-04 |
| Start date | End date |
|---|---|
| 2025-10-06 | 2025-11-04 |
- Computer Assisted Personal Interview [capi]
| Name | Affiliation | Abbreviation |
|---|---|---|
| Namibia Statistics Agency | Government of the Republic of Namibia | NSA |
To ensure the collection of reliable, high-quality, and timely data, a comprehensive series of quality assurance measures were implemented across all levels of the survey. A pilot test was first conducted to evaluate the readiness of the fieldwork tools. These results were then used to refine the questionnaire, the CAPI application, and the training manuals prior to the main fieldwork.
Field staff recruited for the survey underwent an intensive two-week training program, and their final selection for the main fieldwork was contingent upon their performance in written assessments. During data collection, National Supervisors from the head office were deployed to oversee regional 2025 NFIS operations. They ensured that fieldwork proceeded as planned and adhered strictly to prescribed rules and guidelines. By directly observing interviews, supervisors verified that field staff properly introduced the survey objectives and administered questions exactly as trained. This direct monitoring allowed for immediate remedial action, preventing delays and safeguarding data integrity.
Furthermore, collected data was transmitted to the head office daily to mitigate the risk of data loss in the event of damaged or lost tablets. Upon receipt, secondary verification and completeness checks were conducted using the application’s monitoring tool to ensure all transmitted information was accurate, complete, and valid.
Fieldwork Leadership Roles: National Regional Supervisors:
Oversaw 2025 NFIS operations at the regional level.
Regional Statisticians: Supported 2025 NFIS operations at the regional level.
Team Supervisors: Managed 2025 NFIS operations at the Primary Sampling Unit (PSU) level.
To ensure the smooth execution of the 2025 NFIS, the NSA conducted a pilot survey in the Khomas region (specifically in Auasblick and Dordabis) from 21 July to 3 August 2025. The pilot involved two field teams, each assigned to one of the two selected Primary Sampling Units (PSUs). The primary objective was to test the CAPI systems and survey instruments to ensure they accurately captured the intended data. The exercise also evaluated the adequacy of logistical arrangements, administrative support, and the data processing plans. Insights gained from this pilot test were used to refine the survey tools, finalize implementation plans, and accurately estimate the resources required for the main survey.
The main fieldwork was conducted across all 14 regions from 6 October to 4 November 2025. Operations within each region were overseen by a National Supervisor, with support from locally based Regional Statisticians and IT Field Technicians who managed data transmission. The field teams themselves consisted of one team supervisor and two interviewers. Field personnel were deliberately recruited from their home areas to ensure familiarity with the local terrain and to facilitate interviews in local languages.
The data collection work plan was executed in two phases: two weeks dedicated to listing private households within the selected PSUs, followed by approximately three weeks of administering the main questionnaire. A sample of 10 private households was selected per PSU. Both the listing and the main data collection were conducted via face-to-face interviews using a CSPro-based CAPI application administered on tablets.
Data processing
Real-time validation enforced via CAPI (skips, ranges, consistency controls). Postcollection editing included cleaning, inconsistency checks, and supervisory backchecks.
Data Access
| Name | Affiliation | URL | |
|---|---|---|---|
| Namibia Statistics Agency | Government of the Republic of Namibia | https://www.nsa.org.na | info@nsa.org.na |
| Confidentiality declaration text |
|---|
| All information collected that may be linked to individuals or households is treated with strict confidentiality under the provisions of the Statistics Act, 2011 (Act No. 9 of 2011), and used solely for statistical purposes. |
The anonymised microdata generated from this survey will be made available to the public to encourage further research, policy formulation, and analysis purposes only under the following terms and conditions:
- The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of the (NSA).
- The data will be used for statistical purposes only. They will be used sorely for reporting of aggregated information, and not for investigation of specific individuals or organization.
- No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the (NSA).
- No attempt will be made to produce links among datasets provided by the (NSA), or among data from the NSA and other datasets that could identify individuals or organizations.
- Any books, articles, conference papers, theses, dissertations, reports or other publications that employ data obtained from the (NSA) will cite the source of the data in accordance with the citation requirements provided with each dataset.
- An electronic copy of all reports and publications based on the requested data will be sent to the (NSA).
Namibia Statistics Agency (NSA), 2025 Namibia Financial Inclusion Survey (NFIS), Version 1.0 of the public use dataset, 2026.
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data (NSA), the authorized distributors, and the funding agencies bear no responsibility for the use of the data or for interpretations or inferences based upon such uses.
(c) Namibia Statistics Agency (NSA)
Contacts
| Name | Affiliation | |
|---|---|---|
| Namibia Statistics Agency (NSA) | Government of the Republic of Namibia | info@nsa.org.na |