Financial Inclusion Analytics
Quantitative analysis of financial access, digital finance, financial behaviour and related socioeconomic questions.
View case study →Applied research, analytics, evaluation and evidence work across health, development, finance and humanitarian contexts.
This section presents selected examples of how methodological and analytical capabilities have been applied to real research and organisational questions.
A selected portfolio organised around six project categories
These categories provide a practical view of the work and are not intended to represent the complete portfolio.
WHO Public Health Research
WHO-funded research in Kenya examining trust, misinformation, adherence to COVID-19 guidance and vaccine uptake.
View case study →Machine Learning Health Decision Support
A Python-based health analytics and decision-support application with model development, validation and monitoring.
View case study →Selected Evaluation Projects
Selected work on HPV vaccination, vaccine hesitancy, trachoma prevalence, and gender, displacement and healthcare access.
View case study →Baseline & Endline Assessments
Selected maternal, newborn and reproductive-health baselines and endline assessment work in Kenya.
View case study →NGO & Development Research Consultancies
Selected health, humanitarian, displacement and programme-research engagements with development organisations and research collaborators.
View case study →Financial Inclusion Analytics
This project area applies quantitative analysis to questions concerning financial inclusion, digital finance, FinTech, financial behaviour and socioeconomic conditions. It can draw on secondary data analysis and statistical modelling, connecting applied questions with the existing scholarly record in finance and FinTech without treating publications as project deliverables.
- Financial inclusion
- Digital finance & FinTech
- Financial behaviour
- Socioeconomic analysis
- Secondary data analysis
- Statistical modelling
WHO Public Health Research
WHO-funded public-health research in Kenya examined community trust, misinformation and conspiracy theories, adherence to COVID-19 public-health guidance, and vaccine uptake. The analytical contribution included quantitative analysis, interpretation, visualisation and an interactive R Shiny dashboard for evidence discovery and dissemination.
- Quantitative research
- Public-health data analysis
- Epidemiological analysis
- Secondary data analysis
- Statistical modelling
- Research reporting
Machine Learning Health Decision Support
A 2025 health analytics project used Python, statistical modelling, machine-learning model development, validation and performance monitoring to translate analytical output into a web-based decision-support demonstration. It is not presented as a clinical diagnostic or treatment system.
- Health-data analysis
- Predictive modelling
- Machine learning
- Model validation
- Interpretation
- Evidence-informed decision support
Selected Evaluation Projects
Selected engagements include a national HPV vaccination programme review, multi-county vaccine-hesitancy research, trachoma prevalence surveys in South Sudan, and research on gender, displacement and healthcare access. Methods and claims remain bounded by each study design and evidence base.
- Process evaluation
- Outcome evaluation
- Programme-performance assessment
- Pre/post assessment
- Comparative evaluation
- Impact evaluation where supported
Baseline & Endline Assessments
Baseline studies establish programme conditions and indicator values before or near the start of implementation. Endline studies revisit those measures to examine change and programme performance. Selected work includes the Kajiado maternal and newborn health baseline, Child.org’s Pregnant Women’s Group RMNCH endline, and Amref RMNCH service-provision research.
- Establish programme conditions
- Measure agreed indicators
- Compare change over implementation periods
- Assess programme performance
- Inform learning and programme decisions
Assessment to learning
- Baseline
- Implementation
- Midline
- Endline
- Learning
NGO & Development Research Consultancies
Applied research and analytical consulting has spanned selected health, humanitarian, displacement and programme-research engagements. Designs were shaped by each organisation’s question, setting and available evidence rather than a predetermined package.
- Research design
- Quantitative research
- Mixed-methods research
- Programme evaluation
- Secondary data analysis
- Monitoring, Evaluation & Learning
- Evidence synthesis
- Research reporting
A clear route from the research question to useful decision support
The exact workflow depends on the project type, scope, evidence available and decisions the work needs to support.
Problem / Research Question
Methodological Design
Data / Evidence
Analysis
Interpretation
Research or Programme Outputs
Decision Support
Methods selected for the question—not a generic tools catalogue
Established research, analytical, synthesis and evaluation methods may be combined where appropriate to the project design.
- Research design
- Quantitative research
- Mixed-methods research
- Statistical analysis
- Statistical modelling
- Secondary data analysis
- Machine learning where appropriate
- Evidence synthesis
- Programme evaluation
- Monitoring, Evaluation & Learning
- Data visualisation
Substantive settings for selected and potential applications
These are domains across which selected work has been undertaken or in which the methods may be applied; they are not claims that every approach is suitable in every setting.
- Public Health
- Clinical & Health Research
- Financial Inclusion & FinTech
- Development Economics
- Humanitarian Research
- Monitoring, Evaluation & Learning
- Data Science & Analytics
Applied work can connect with several forms of research evidence
Depending on its purpose and scope, an applied project may contribute to a peer-reviewed publication, research report, analytical output, programme evidence, or policy and decision-support material. Not every project results in a publication.
Combine service areas around the evidence need
Project implementation may bring together multiple service families depending on the question, methods, data and intended use.
Research & Evaluation
Research design, quantitative methods and evaluation aligned with the question and evidence available.
View service areaEvidence Synthesis
Structured approaches to finding, appraising and integrating existing evidence.
View service areaData Science & Analytics
Statistical analysis, modelling and responsible machine learning for analytical questions.
View service areaMonitoring, Evaluation & Learning
Measurement systems, programme evidence and learning processes that support better decisions.
View service areaHave a research, analytical, evaluation or evidence project in mind?
Support may range from methodological design and data analysis to evidence synthesis, evaluation and Monitoring, Evaluation & Learning.