Terms of Reference. Poverty Mapping and Welfare Estimation Combining Mobile Phone and Remote Sensing Data

Transcription

1 Terms of Reference Poverty Mapping and Welfare Estimation Combining Mobile Phone and Remote Sensing Data 1 Institutional Background IFC MCF Partnership for Financial Inclusion The International Finance Corporation (IFC), a member of the World Bank Group, is the largest global development institution focused exclusively on the private sector in developing countries. It utilizes and leverages its own products and services as well as products and services of other institutions in the World Bank Group to provide development solutions customized to meet clients needs. Applying its financial resources, technical expertise, global experience, and innovative thinking, the IFC helps partners overcome financial, operational, and political challenges. Clients view IFC as a provider and mobilizer of scarce capital, knowledge, and long-term partnerships that can help address critical constraints in areas such as finance, infrastructure, employee skills, and the regulatory environment. In cooperation with the MasterCard Foundation (MCF), IFC is implementing The Partnership for Financial Inclusion ( the Partnership ), a joint initiative to expand microfinance and advance digital financial services in Sub-Saharan Africa. The seven-year program was launched in January 2012, and works with microfinance institutions, banks and mobile network operators across the African continent to develop and test innovative business models for financial inclusion. The Partnership also pursues an extensive applied research and integrated Monitoring, Evaluation and Learning (MEL) agenda, harnessing and sharing insights gained in program projects for the industry and the public good. As such, the program aims to have an impact even beyond direct projects to help achieve universal financial access by Project Background Poverty Mapping and Welfare Estimation combining Mobile Phone and Remote Sensing Data The subject of data is increasingly gaining prominence as the global production of data is growing at exponential volumes and greater complexity. The opportunity to mine that data and to apply the latest data science and machine learning methods has enormous potential for governments, firms and customers. But although the use of data holds huge opportunity its value is often still uncaptured for the public and private sectors. Further, with the advent of personal cell phones and the growth of technology advancing to a level where individuals can produce extraordinary amounts of data and the ability to store that data the field of data science is still quite new and also brings many questions. There is however an enormous potential to leverage the data revolution for positive, sustainable development. The IFC-MasterCard Foundation Partnership for Financial Inclusion is perfectly positioned to engage in this data revolution by supporting digital financial services clients to take the lead as early adopters, leveraging technology and data to unlock value by strategically, efficiently reaching customers at the bottom of the period for sustainable financial inclusion. To measure who is benefitting from financial inclusion and to determine and monitor the reach of low-income target groups, it s necessary to measure welfare and poverty levels regularly, at 1

2 high spatial resolution, at high temporal frequency, and at low cost. In recent years, the analysis of day and night time satellite imagery with deep learning algorithms has provided new methods to predict poverty and welfare levels. At the same time, volumes of cell phone data become increasingly available which presents an exciting opportunity for new precise and improved low cost poverty estimation models. This project is implemented through the Partnership s applied research and MEL program. Funding Sources for this assignment are provided by: MasterCard Foundation, as implemented through the IFC-MasterCard Foundation Partnership for Financial Inclusion research program. MasterCard Foundation is an independent non-profit organization based in Toronto, Canada. Additional funding may be provided through Bill & Melinda Gates Foundation, as implemented through the IFC-MasterCard Foundation Partnership for Financial Inclusion research program. The Bill & Melinda Gates Foundation is an independent non-profit foundation (charitable trust) based in Seattle, USA. 3 Description of the assignment IFC is looking for Consultant(s) that will combine remote sensing data and satellite imagery data with CDR/mobile phone data to develop computational models for poverty mapping and welfare estimation in small areas and at the household level. The assignment will start with exploring poverty mapping and welfare estimation with big data sets of mobile phone data (call detail records and mobile money transactions) in Uganda. Analysis will also incorporate survey data, where applicable, including household surveys conducted through other research activities. Ultimately, the approach might be replicated for other markets, and these opportunities should be assessed. The project and model might be expanded to include data from additional other markets in Sub-Saharan Africa such as Ghana, Cameroon or Lesotho; most likely Ghana. These models and associated analysis are expected for two countries, starting with Uganda. 4 Objective of the assignment and research questions Develop and explore the combination of mobile-phone data and satellite-based methods for improved poverty and welfare estimation in at least two Sub-Saharan African countries. To generate learning on drivers for scale and growth of DFS services and their impact on consumers, particularly on poverty and welfare. To produce research suitable for academic journals and publication and public knowledge dissemination. The research will focus on answering the below research questions: (1) How can phone and satellite-based methods be optimally combined to generate accurate measures of poverty and welfare; both with respect to individual DFS subscribers, and local and regional geographic zones? (2) Can these methods - and in particular satellite-based approaches -- generate accurate household-level estimates of welfare? (prior work has focused on small regions); and what patterns, customer segmentation, localization or networks are evidenced between welfare estimates, DFS use; and DFS and GSM subscribers? (3) Addition - Can such phone and satellite based data be used to accurately infer changes over time in the welfare of individuals, households, and villages? And is there evidence that localized welfare estimates change over time with the introduction, usage, or transaction volumes associated with DFS services. 2

3 4.1 Methodology Rather than being prescriptive about which data analysis and approach is required, the technical proposal of the Consultant(s) is scored by the usefulness, creativity and innovativeness of the methodology to answer the research questions of interest, the wealth of information that is going to be provided, the prior track record of high-quality research, and the sort of strategic insights and content that are to be expected from the interim and final analysis. The following rough steps are expected to be part of the analysis process: (1) Extraction, Transformation, and Loading (ETL) of Mobile Network Operator s transactional databases. (2) Satellite imagery geo-spatial poverty estimation models (3) Combination of satellite imagery, mobile phone data and available survey data from MEL research team or 3 rd party providers to deliver a geo-localized map of poverty and welfare estimates (4) Aggregation, segmentation and pattern analysis a. Intensity of mobile phone use b. Nuanced patterns of phone activity c. Physical location and mobility d. Additional metrics to be determined (5) Descriptive and Predictive Analytics of Poverty and Welfare levels of individuals, households and villages (small areas) Consultant(s) are expected to propose improved or different methodology, modeling approaches, and steps in their technical proposal if deemed relevant and useful for this assignment. 4.2 Deliverables (1) Inception Report Finalized project design and research plan. Including data inventory report of data that will be used (mobile phone data & satellite imagery) during subsequent analysis and results of desk research on similar work and approaches to poverty and welfare estimation to date. (2) Quarterly Updates Quarterly updates on progress made including interim results (presented in appropriate visualizations and maps) as well as a documentation of any ongoing challenges (if the case). Can be shared in PowerPoint format or other formats, of modest length or formality. Research progress, incremental learning, innovative methods, key observations, lessons learned to-date or other relevant information suitable for internal knowledge sharing is expected at intervals not less than 3 months. (3) Interim Reports - Presenting interim and aggregated results in visualizations, maps and write ups that provide operationally relevant results to report back to mobile phone data provider. Interim reports are expected to be formal reports, with focus on specific project facets relevant given the state of the research. 3

4 (4) Final Report The final report should answer the primary research questions, provide results and conclusions from detailed analysis. The process will include a general outline well-advanced of the final report; followed by an initial draft, permitting substantive time for comments. (5) Final Results Data set(s) relevant for poverty estimates, and the model(s) developed to yield these estimates; and mobile phone users and/or geographic areas should supplement the final report, which would discuss these data and their implications; and the models and associated report on modelling methods. (6) Codes, Models & Scripts Consultant(s) are expected to share analysis code and scripts used for data analysis. Intermediate results should be included in Quarterly Updates. Final results should be replicable with all information, code and data shared during the cause of the project. Any proprietary or pre-existing intellectual property should be pre-identified and listed for non-disclosure as part of the technical proposal. The final report should reflect on usage or implementation requirements for codes, models and scripts, or other utilities that might be developed in the course of the assignment, such as dashboards or visualizations. (7) Journal Publications The research aims to yield learning suitable for academic publication(s), for which the Consultant(s) are expected to co-author drafting and lead publication processes in collaboration with IFC project team. 4.3 Timeline The assignment has a timeline of 14 months. A tentative timeline for activities and deliverables is presented below. Tentative schedule of activities and deliverables A Data Sharing (IFC with Consultant(s) Mobile phone data, HH survey data & polygons of interest for small area poverty estimation) B Inception Report C Quarterly Update Reports D Interim Reports E Final Report F Sharing Code & Scripts G Publication Process Month Consultant(s) are expected to provide first tangible results after 6 months apart from the inception report as well as regular quarterly updates. 5 Administrative information 5.1 Reporting The Consultant(s) are solely responsible for the quality and timely completion of all tasks and deliverables defined by these Terms of Reference. The Consultant will report to the Task Managers Soren Heitmann, based in Johannesburg, South Africa, and Sinja Buri, based in Dakar, Senegal. The overall research design and technical implementation expects a collaborative engagement and flexibility appropriate for a research project. Regular status meetings and collaborative problem-solving are expected as part of the engagement. Should it be necessary to significantly 4

5 modify the scope of work, budget, or timeline, the Consultant(s) must discuss the circumstances with the Task Managers, and obtain their prior written approval. 5.2 Inputs provided by IFC In order to facilitate the Consultant(s) to carry out the assignment described above, IFC will provide the Consultant(s) with: (1) Datasets from mobile network provider(s) from at least one African country (Uganda). Data from provider(s) in other African countries might be added during the course of the project, likely for Ghana, Cameroon or Lesotho. And any supplementary data, such as for household surveys. (2) Facilitation and coordination of contract with the Mobile Network Operator in Uganda whose data will be used for this assignment; and that of other MNO in secondary country. (3) An IFC contact to provide technical assistance on demand along the project. (4) Other administrative assistance as necessary and appropriate. (5) In collaboration with the Consultant(s), IFC may provide additional team capacity to support the research project. 5.3 Inputs provided by Consultant(s) Consultant(s) are expected to provide satellite imagery data and/or other datasets necessary for the adequate functioning of the poverty models. Consultant(s) are expected to provide technical computing infrastructure necessary to run the models and big data analysis (terabyte level big data ), and/or to specify technical resource requirement gaps as part of the technical proposal. 5.4 Payment modalities This consultancy is a lump sum contract (including VAT), so financial proposals should include all personnel, travel, printing and other costs associated with this consultancy. The following proportions of the lump sum amount will be payed upon reception of the listed deliverables (Acceptance for journal publication will not be deemed a requirement for final payment, should quality submission(s) be rejected): (1) 10% upon Inception report (2) 4 x 10% respectively upon Quarterly Update Reports (3) 2 x 15% respectively upon Intermediate Deliverables after 6 & 12 months. (4) 15% upon Final Report, Data Results and Models (5) 5% after finalization all deliverables 5.5 Proposal requirements The submitted proposal should contain 2 components (1) The technical proposal should describe in detail the understanding of the Firm regarding the objective described in these Terms of Reference. The Firm should also provide details on the strategies proposed to achieve project objectives for key elements of the assignment, including first tangible results after 6 months into the project. 5

6 Responsibilities of each members and a selection of relevant experiences with similar work, should be presented in an annex. (2) The financial proposal shall detail costs for each deliverable for each phase. Costs related to the delivery of the project and costs of service should be presented separately. Costs and activities of each member of partners or sub-contractors should also be presented separately. Any administrative costs associated with the management of the project award should be specifically enumerated. Financial proposals should accommodate the non-profit funding sources associated with this assignment; and IFC s designation within the World Bank Group as an International Organization and Specialized Agency of the United Nations. Technical and financial proposal should be written in English. The technical proposal should not exceed 20 pages, excluding annexes. 5.6 Consultant(s) Qualifications The selected consultant company and consultant(s) that will be hired to provide above described technical input and advice should have the following qualifications: (1) Internationally-recognized expertise and experience in applied data science particularly in the areas of big data and more generally different approaches to business/data analytics for private sector clients. (2) Prior research experience in the areas of Digital Financial Services. (3) Excellent expertise and proven track record in developing computational models based on satellite imagery and mobile phone data for welfare and poverty estimation. (4) Excellent expertise and proven track record in data science and big data analytics (5) Self-developed material that can serve as input for this collaboration would be a plus. (6) Ability to work effectively toward tight deadlines and to deliver all deliverables in English. (7) Ready for flexible, close and explorative nature of research collaboration. (8) Demonstrated excellent understanding of the assignment. (9) Direct availability to work on the assignment. 5.7 Evaluation Criteria Technical proposals will be evaluated along the following evaluation criteria: (1) Adequacy of the methodology and the proposed work plan in responding to the Terms of Reference. (2) Experience of the Consultant(s) specifically related to this assignment. a. Experience in the analysis of satellite imagery for welfare estimation. b. Experience in the analysis of mobile phone data for welfare estimation. c. Experience of working with large scale data sets d. Demonstrated track record of high-quality research publications (3) Qualifications and competence of the key staff related to this assignment. 6