GIS Mapping for Financial Inclusion Training Course

Participants can organise a GIS project and select appropriate spatial data structures.

• Vector, raster and tabular data structures for financial inclusion projects
• Points, lines and polygons representing services, roads and populations
• Layer order, symbology and attribute tables in GIS projects
• Coordinate reference systems and geographic versus projected coordinates
• Map scale, spatial resolution and their effects on interpretation
• Project folders, naming conventions and reproducible file management

Participants can source, assess and document spatial datasets for an inclusion study.

• Access-point registries from banks, agents, regulators and payment providers
• Census, poverty and population datasets for demand-side analysis
• OpenStreetMap roads, buildings and points of interest assessment
• Satellite imagery sources for settlement and infrastructure observation
• Metadata records using ISO 19115 data documentation principles
• Data licensing, source attribution and permitted reuse conditions

Participants can produce an analysis-ready geocoded register of financial service points.

• Address standardisation before geocoding branch and agent records
• Geocoding methods using addresses, landmarks and administrative locations
• Coordinate format checks for decimal degrees and projected coordinates
• Duplicate detection using names, addresses and spatial proximity
• Attribute-domain rules for provider, channel and operating status
• Outlier review for misplaced coordinates and implausible locations
• Geocoding confidence scores documented for subsequent quality review

Participants can evaluate spatial-data fitness and manage household location-data risks.

• Positional accuracy, completeness, timeliness and logical consistency measures
• Sampling bias in agent registries and household survey locations
• Missing-data patterns assessed through attribute completeness profiles
• Personal data minimisation for household and customer coordinates
• Informed consent and purpose limitation for location collection
• Aggregation, masking and suppression methods for sensitive map outputs

Participants can create clear baseline maps of financial service distribution and access gaps.

• Choropleth maps using rates rather than raw population counts
• Graduated symbols for branches, agents, ATMs and mobile-money outlets
• Jenks, quantile and equal-interval classification method selection
• Bivariate maps comparing poverty incidence with service-point density
• Density surfaces showing clustered financial-service provision patterns
• Map layouts with scale bars, legends, sources and uncertainty notes

Participants can estimate simple geographic access to formal financial services.

• Euclidean distance calculated between settlements and service access points
• Fixed-distance buffers for first-pass branch and agent coverage estimates
• Dissolved buffers preventing double-counting within overlapping service zones
• Population counts intersected with covered and uncovered areas
• Distance thresholds justified through local travel and policy evidence
• Coverage results segmented by provider, channel and administrative area

Participants can model realistic travel-time access using road and path networks.

• Road-network topology checked for disconnected segments and incorrect intersections
• Travel speeds assigned by road class, terrain and transport mode
• Network service areas generated for defined travel-time thresholds
• Origin-destination matrices calculating settlement-to-service travel times
• Walking, motorbike and public-transport assumptions compared for rural access
• Seasonal road disruption incorporated into accessibility scenario analysis
• Travel-time maps interpreted alongside service capacity and opening hours

Participants can interpret remote-sensing layers to improve inclusion mapping evidence.

• Optical satellite imagery interpreted for settlements, roads and land cover
• Spatial resolution matched to village, neighbourhood and regional questions
• Cloud cover, acquisition dates and seasonal effects on imagery selection
• Land-cover classification used to distinguish built-up and agricultural areas
• Night-time lights assessed as a proxy for economic activity
• Digitising settlement extents from imagery and local reference layers

Participants can map population groups facing heightened barriers to financial access.

• Population grids allocated across accessible and underserved service areas
• Poverty, gender, age and disability indicators mapped responsibly
• Small-area indicators normalised using rates, ratios and denominators
• Composite vulnerability indices built from documented indicator weights
• Hot spot analysis identifying statistically concentrated inclusion barriers
• Priority populations distinguished from simply high-population locations

Participants can calculate and map indicators for financial-service availability and reach.

• Access-point density expressed per 10,000 adults and square kilometre
• Median travel time calculated for settlements and population groups
• Account ownership indicators joined to spatial administrative units
• Agent activity rates separated from registered agent counts
• Gender-disaggregated access indicators compared across mapped districts
• Scorecard thresholds documented for transparent management reporting

Participants can identify and rank candidate locations for financial service expansion.

• Multi-criteria decision analysis for branches, agents and cash points
• Weighted overlay combining population, demand, access and competition criteria
• Analytic Hierarchy Process weights elicited through pairwise comparison
• Exclusion zones defined around unsuitable, restricted or saturated locations
• Candidate sites ranked using documented suitability scores
• Sensitivity analysis testing how weight changes affect rankings
• Site recommendations checked against field intelligence and operating constraints

Participants can assess channel footprints and formulate geographically grounded expansion options.

• Channel mix assessed across branches, agents, ATMs and merchant points
• Catchment overlap measured between competing and same-provider access points
• Agent cannibalisation risks identified through proximity and transaction patterns
• White-space analysis locating demand beyond existing service catchments
• Branch rationalisation scenarios tested against travel-time access consequences
• Expansion phasing aligned with population, infrastructure and market readiness

Participants can design a field-validation process for mapped financial inclusion evidence.

• Field forms designed for service availability, activity and customer observations
• KoboToolbox location questions configured with validation and consent statements
• Sampling frames selected for agent verification and settlement observations
• Ground-truth protocols comparing mapped records with field conditions
• Enumerator quality controls using timestamps, photographs and coordinate checks
• Field corrections reconciled with master access-point datasets

Participants can present spatial evidence with clear limitations and actionable recommendations.

• Decision-focused map narratives structured around questions, evidence and actions
• Executive map briefs distinguishing findings, assumptions and recommendations
• Uncertainty communicated through source notes, confidence labels and caveats
• Provider comparisons presented without disclosing commercially sensitive locations
• Dashboard metrics selected for management and regulatory reporting cycles
• Recommendations prioritised by impact, feasibility, cost and implementation ownership

Participants can establish a practical workflow for repeated financial inclusion mapping cycles.

• GIS operating model defining data owners, analysts and decision authorities
• Update schedules set for access points, population data and imagery
• Data governance controls covering access permissions and version histories
• Quality assurance checkpoints embedded before map publication and decisions
• Key performance indicators linked to expansion and inclusion targets
• Implementation roadmaps sequencing pilot areas, resources and review milestones

Participants can build, review and present a complete financial inclusion mapping analysis with prioritised actions.

• Project scope defined around a realistic financial inclusion decision question
• Access-point, population and network datasets prepared for integrated analysis
• Coverage, travel-time and vulnerability indicators calculated and mapped
• Suitability model developed for priority branch or agent locations
• Data-quality, privacy and methodological limitations documented clearly
• Map portfolio reviewed against stakeholder decision requirements
• Findings presented with phased recommendations and implementation measures