www.ifc.org/thoughtleadership NOTE 86 • JUNE 2020 Leveraging Big Data to Advance Gender Equality By Ahmed Nauraiz Rana Gender equality and the empowerment of women and girls, one of the Sustainable Development Goals, is a highly complex and challenging undertaking. We must address multiple issues— discrimination, violence, education, employment, economic resources, and technology—and work across economic sectors, from agriculture to financial services. Achieving gender equality will require significant amounts of accurate data about the situations and struggles of women and girls. Globally, however, there is a major gap in data that is disaggregated by sex, and this gap often renders women’s societal, cultural, and economic contributions and obstacles practically invisible. It can also exacerbate existing gender divides, feeding and reinforcing biases in social programs, access to financial and other services, economic opportunities, and even development programs designed to address gender inequality. Part of the solution may be in the form of big data, which, if used effectively, can provide the volume of data needed to portray women and their situations accurately, which in turn can inform the creation of evidence-based solutions. The social and economic integration of women into society Discrimination against women is a multifaceted phenomenon is increasingly becoming part of all development discourse. that spans economic sectors and is ingrained in societal Various mechanisms are being employed around the world to practices. Issues such as land rights, access to education, shed light on the issues and inherent biases that women are financial inclusion, healthcare, gender-based violence, family subjected to, and numerous interventions focused on greater planning, and many others can only be correctly addressed gender equality are being implemented. But the success of all if evidence-based policies are formulated and progress is these efforts is dependent on data that is verifiable, reliable, monitored in a quantifiable manner. and ensures integrity. Just 21 percent of the data required to This is contingent on the use of big data—extremely large monitor 54 gender-specific indicators within the Sustainable data sets that can be analyzed for patterns and trends. Development Goals (SDGs) is current.1 However, up-to-date data exists for only a small fraction Additionally, the overrepresentation of men in the tech field of indicators that were developed to evaluate SDG #5, filters into content creation, with recommendation algorithms Gender Equality. As a result, most countries have never been often trained on male-majority data. As a result, disaggregating able to measure more than three of the 14 indicators that data based on gender is critical to understanding how developing were created to assess progress toward this goal. 2 Clearly, countries can help women living on the border between poverty innovative approaches are needed to ensure effective data and prosperity. Gender equality is a fundamental prerequisite for collection that is disaggregated by sex, which is defined by the multiple development goals, so it is imperative to emphasize the United Nations as “data collected and tabulated separately for fact that progress will falter without a data-driven focus. women and men.”3 About the Author Ahmed Nauraiz Rana, Associate Digital Economy Officer, Gender and Economic Inclusion Group, Economics and Private Sector Development, IFC. His email is arana4@ifc.org. 1 This publication may be reused for noncommercial purposes if the source is cited as IFC, a member of the World Bank Group. For private sector businesses, sex-disaggregated data is a level of gender equality alone will add $28 trillion to global necessity where the aim is to build consumer-centric business GDP by 2025. 5 The revenue share was estimated to be higher strategies and enhance the company’s value proposition to for tech companies, start-ups, and industries where innovation specific market segments, including the women’s market. It is the key to growth, highlighting the fact that greater allows for the recognition of customer segmentation and the gender equality is not just desirable but is an integral part of market opportunity.4 successful revenue-generating businesses. Inclusive approaches to gender data collection and usage have The data revolution currently underway can—and in certain been shown to yield greater revenues, as well as numerous places already is—being leveraged to achieve sustainable other nonfinancial positive outcomes such as employee development goals pertaining to gender rights and equality. In 2017, for example, the Bill & Melinda Gates Foundation retention, and operational replicability and scalability. launched a tech initiative in partnership with UN Women Furthermore, a number of existing studies have identified to help countries improve the quality of gender-specific data various avenues through which sex-disaggregated data can collected globally.6 Similarly, the United Nations Foundation assist women entrepreneurs in overcoming barriers to market spearheaded Data2X, a technical platform initiative to access, financial inclusivity, and identification of prospective help close the daunting gender data gap in five development opportunities, and address value-chain bottlenecks using domains—health, education, economic opportunity, political gender-specific information. participation, and human security—by collaborating with McKinsey Global Institute estimated that an increase in the government agencies and the private sector.7 FIGURE 1 Current Data Sources for Big Data Human sourced data Process mediated data » social media » health records » blogs » mobile phone data » vlogs » credit card data BS » internet forums » public transport » wikis M CO usage data » internet searches U » job application records » email or SMS content » chips identifcation data CR M OCITY » e-government data MU VE E M L L LU DIGITA NITIE VO Machine generated data » road sensor data » smart meter electricity data S » scanners data » satellites imagery/aerial imagery data » traffic loops webcams data » vessel identification » internet of things (IoT) Media sourced data Crowdsourcing data VA R I E T Y » TV and radio » citizen-generated data CAP broadcast data » images collection A CITIES » podcast data » volunteered geographical » digital newspapers information (VGI) Source: United Nations Entity for Gender Equality and the Empowerment of Women, also known as UN Women. 2 This publication may be reused for noncommercial purposes if the source is cited as IFC, a member of the World Bank Group. How Can Big Data Support Gender Equality? understand the role of big data in evaluating women’s political participation and leadership found that the analysis and Traditional data collection methods include surveys, interpretation of conversations within a cultural context can be interviews, and focus groups, among others. However, these significantly enhanced by focus groups with social media users.8 methods have shown limitations in their ability to collect quality data about female subjects and target groups. They Areas of Intervention – Current Trends have also been found to incorporate stereotypes and other Geospatial data accessed via satellite imagery can be leveraged socio-cultural factors that induce gender biases. Such barriers to predict women’s wellbeing. A number of research studies raise valid concerns about construct and external validity, and have found social and health indicators such as child stunting, lead to incomplete or inaccurate information that obstructs infertility, literacy, and access to contraception to be correlated both the formulation of evidence-based policies and the with geospatial factors such as climate, elevation, aridity, determination of the root causes of gender discrimination. and geographical location.9 And it is relatively easy to map Big data allows researchers and policy makers to transcend such geospatial factors across countries and complement that ineffective means of data collection. It offers policymakers and data with information gathered via demographic and health investors alike an additional evidence base and complements surveys (DHS). This allows for the modelling of possible traditional forms of data collection. In recent years big data wellbeing indicators where data from DHS is not readily has evolved as a parallel source for understanding gender available, transforming inaccessible and neglected areas into a perceptions and forms of discrimination and marginalization continuous landscape of information for gender wellbeing. due to its ability to detect large-scale data patterns and generate Similarly, mobile phone data can be leveraged to make better- predictive models. A study commissioned by UN Women to informed decisions regarding women’s social protection. A study commissioned by the Massachusetts Institute of Technology in collaboration with UN Global Pulse used data Coping With COVID-19 Through a BOX 1 from credit cards and mobile phones to identify patterns of Gender Lens women’s spending and physical mobility.10 Using these to The COVID-19 pandemic poses a serious threat to project women’s economic status, researchers were able to women’s employment and livelihoods due to its identify seven economic lifestyle clusters among women in the potential to exacerbate preexisting inequalities and reinforce gender gaps in social, political, and economic dataset. The categorization of clusters allowed development systems. From a lack of access to health services, social professionals to understand individuals’ economic status protections, and digital technologies, to a significant and needs. The technique helped identify women who were rise in domestic violence and unpaid care work, the more vulnerable to economic downturn and shock, and impacts of COVID-19 are being felt acutely by women improved targeting methods and interventions for extending around the world. Recognizing the range of gender- socioeconomic protections. based differences in the implications of the crisis is critical to ensuring that men and women have equal Big data extracted from patterns of Internet use also aids in opportunity to benefit from response efforts and can monitoring women’s mental health. Most publicly available participate in the eventual economic recovery. mental health data does not include sex-disaggregated As economies around the world gradually recover, it information, yet there is a significant need for gender specific is advisable for private sector firms to fill information mechanisms for data collection and analysis. Internet use gaps by leveraging sex-disaggregated data as they data can be leveraged to analyze the expression of thoughts begin the work of rebuilding a resilient economy. on social media platforms and provide insights into women’s Assessing the gender-differential business impact of mental health and welfare. To this end, researchers at UN COVID-19 is absolutely essential to creating effective strategies and designing crisis solutions that meet Global Pulse successfully employed artificial intelligence the needs of both female and male entrepreneurs. machine-learning techniques to determine if expressions of Similarly, in order to develop a diverse and inclusive distress or anxiety on social media accurately identified mental workforce that is resilient to another such crisis, health disclosures. They analyzed publicly available tweets it is imperative to collect, analyze, and utilize sex- from women and girls in India, South Africa, the United disaggregated data to better understand gaps Kingdom, and the United States to locate signals of depression and how they might lead to lower productivity or and make appropriate and targeted recommendations.11 profitability at the firm level. Of the many challenges that women face, one of the most staggering is access to financial services. For example, in 3 This publication may be reused for noncommercial purposes if the source is cited as IFC, a member of the World Bank Group. Senegal some 87 percent of women lack access to any formal collect data via SMS messages in local dialects from radio financial products or services.12 This financial exclusion can be audiences. The data that was collected was instrumental in attributed both to gender discrimination and to a lack of data generating insights regarding cultural beliefs and practices and that may prevent financial institutions from making sound was further used to develop gender equity programs and map decisions. This lack of financial inclusion thus directly impacts health vulnerability areas.16 women’s ability to improve their earning capacity and engage Identifying Trends in Workplace Discrimination. This in entrepreneurial activities, making them more vulnerable to combined initiative by UN Global Pulse, the International economic shocks and downturns. An analysis of the Senegal Labour Organization, and the Government of Indonesia was River Valley rice value chain by Feed the Future revealed designed to address discriminatory behavior against women that financial institutions were hesitant to lend to female in the workplace in Indonesia. Researchers collected and rice farmers due to perceived high risk, a lack of available analyzed data from publicly available tweets over three years collateral, and most important, a lack of information that to identify real-time signals of discrimination. The data helped prevents financial institutions from being able to evaluate risk understand women’s unwillingness to report experiences and tailor lending terms to female consumers.13 related to discrimination and violence in the workplace.17 Such a lack of information is not unique to agricultural Mapping Indicators of Women’s Welfare: Literacy, Stunting, lending; it occurs across economic sectors. Readily available Poverty, and Maternal Health. An initiative of World Pop/ data on key transaction factors can help address many of the Flowminder and Data2X is developing modelling techniques concerns of financial services suppliers. that use high-resolution geospatial data to infer similar high- resolution patterns of social and health phenomena across Data Innovation Projects Advancing Gender entire countries. Based on deduced correlation, the method Equality is used to predict social and health outcomes where surveys Various other projects using big data to address gender have not been performed, generating a series of highly detailed inequality issues have been undertaken. The following are a maps that illustrate landscapes of gender inequality, including few of them. stunting, literacy, and the use of modern contraceptives.18 Discovery of Complex Anomalous Patterns of Sexual Big Data and the Cloud: Piloting eHealth. The Government Violence in El Salvador. A Carnegie Mellon University of Ghana, in partnership with the World Bank Group, project applied data mining techniques to uncover complex implemented a performance-based financing project in anomalous spatio-temporal patterns of sexual violence. The four regions with particularly poor maternal child health researchers identified patterns after analyzing data on rape nutrition outcomes to incentivize community health teams to incidents in El Salvador over a period of nine years. These improve female health outcomes. The quantity and quality of patterns helped formulate real-time early detection that performance-based indicators was assessed by means of data would allow law enforcement agencies to initiate early rapid collected directly from beneficiary communities, using an response.14 Android-based survey tool.19 The Everyday Sexism Project is an initiative by the Oxford Girl Effect’s Springster Mobile Platform. Researchers from Internet Institute to create a semantic map of sexism via the Girl Effect have been using a wide range of techniques to application of a natural language processing approach that comprehend how user engagement affects girls’ lives after analyzes a large-scale, crowd-sourced dataset on sexism they engage in conversations with other users, and/or read collected from the project website. The goal is to develop content on Springster, a global mobile-first platform developed an advanced sociological understanding of women’s life for confidence and skill development of vulnerable girls aged experiences of sexism and compute a methodological, evidence- 14 to 16. Researchers have been using Google Analytics, based approach for modelling relevant interventions.15 comment analysis, online surveys, and social media analytics Two-way Radio: Engagement with Somali Women. Africa’s to combine big data with traditional approaches to find Voices, a University of Cambridge tech startup, designed innovative and improved ways of influencing positive change five interactive radio shows on gender and child protection and strengthening female image building in an online space. 20 issues to address the gaps in data and evidence pertaining Measuring Economic Resilience with Financial Transaction to (i) female genital mutilation/cutting, (ii) child marriages, Data. The project, undertaken by BBVA Analytics, explored (iii) girls’ access to education, and (iv) juvenile justice. The ways that financial transaction data could be analyzed to show was broadcast across 27 stations and was leveraged to determine the level of economic resilience of people affected 4 This publication may be reused for noncommercial purposes if the source is cited as IFC, a member of the World Bank Group. by natural disasters. It did not focus solely on women but did challenging due to the high associated costs and technical incorporate a gender lens that revealed differences in how expertise required to retrieve scattered information. However, women and men are impacted, including their differences given these considerations, big data analytics has enormous in coping and recovery mechanisms. The project used the potential for policy makers and investors as a fast-evolving Mexican state of Baja California Sur as a case study to source of information that can be leveraged to gain valuable assess the impact of Hurricane Odile on livelihoods and insights regarding women and girls. economic activities over a period of six months. The project ACKNOWLEDGMENTS team measured daily point-of-sale transaction and ATM The author would like to thank the following colleagues for withdrawals at high geo-spatial resolution to gain insights into their review and suggestions: from Gender and Economic the way people prepare for and recover from disasters. Findings Inclusion Group, Economics and Private Sector Development, revealed that women increased their spending twice as much as IFC: Henriette Kolb, Manager; Alexa Roscoe, Digital Economy men in preparation for the disaster, and that they took much Lead; Charlotte Benedicta Ntim, Digital Economy Officer; longer than men to fully recover from it. These findings are from Telecom, Media, Technology, Venture Capital and Funds, instrumental as a starting point to design programs to assist Sector Economics and Development Impact, Economics and rehabilitate women after natural disasters.21 and Private Sector Development, IFC: Davide Strusani, Principal Economist; Georges Houngbonon, Economist; and Conclusion Thomas Rehermann, Senior Economist, Thought Leadership, Big Data can play a fundamental role in achieving gender Economics and Private Sector Development, IFC. equality and empowering women and girls across the globe Please see the following additional reports and by identifying multi-sectoral gaps in the provision of equal EM Compass Notes about technology and its role in opportunities and the protection of female rights, and by emerging markets: Reinventing Business Through Disruptive aiding in the implementation of evidence-based policies and Technologies - Sector Trends and Investment Opportunities for Firms interventions. Data from sources such as radio transmissions, in Emerging Markets (March 2019); Blockchain: Opportunities social and digital media, call records and mobile network for Private Enterprises in Emerging Markets (January 2019); operations, and satellite imagery, both alone and in Accelerating Digital Connectivity Through Infrastructure Sharing combination with traditional data sources, can help highlight (Note 79, February 2020); Artificial Intelligence and the Future the needs and concerns of women and girls. However, it is for Smart Homes (Note 78, February 2020); Artificial Intelligence important to be cautious of the limitations and concerns and 5G Mobile Technology Can Drive Investment Opportunities that big data poses, including careless interpretations that in Emerging Markets (Note 76, December 2019); How Artificial Intelligence is Making Transport Safer, Cleaner, More Reliable and can lead to disproportionate representation and biased Efficient in Emerging Markets (Note 75, November 2019); Bridging recommendations. the Trust Gap: Blockchain’s Potential to Restore Trust in Artificial Data collection and processing requires an adequate Intelligence in Support of New Business Models (Note 74, Oct 2019); framework, extensive digital infrastructure, stringent Artificial Intelligence: Investment Trends and Selected Industry Uses regulations for privacy protection, and tools to mitigate (Note 71, Sept 2019); The Role of Artificial Intelligence in Supporting risks of harm to data subjects. Access to big data is also Development in Emerging Markets (Note 69, July 2019). 1 Mohapatra, Arti and Lauren Shields. 2018. “Can Data Improve the Lives of Women Around the World?” GreenBiz, 9 August 2018. https://www. greenbiz.com/article/can-data-improve-lives-women-around-world. 2 Suzman, Mark. 2017. “Data Driven Gender Equality.” World Economic Forum, 18 September 2017. https://www.weforum.org/agenda/2017/09/gender- equality-it-starts-with-data. 3 United Nations Statistics Division. “Gender Statistics Manual – Integrating a Gender Perspective into Statistics.” https://unstats.un.org/unsd/ genderstatmanual/What-are-gender-stats.ashx 4 FAO. 2019. “Sex-disaggregated data in agriculture and sustainable resource management: New approaches for data collection and analysis.” Rome. 2019. http://www.fao.org/3/i8930en/i8930en.pdf. 5 Executive Briefing. “The Power of Parity.” McKinsey Global Institute. https://www.mckinsey.com/featured-insights/employment-and-growth/the-power- of-parity-advancing-womens-equality-in-the-united-states. 6 United Nations Entity for Gender Equality and the Empowerment of Women. 7 Noble, Eva. 2018. “Without Data Equality, There will be no Gender Equality.” Women Deliver, 11 June 2018. https://womendeliver.org/2018/without- data-equality-there-will-be-no-gender-equality/. 8 Lopes, Claudia and Savita Bailur. 2018. “Gender Equality and Big Data.” UN Women, January 2018. https://undg.org/wp-content/uploads/2018/02/ Gender-equality-and-big-data-en.pdf. 9 Rogers, Kelli. 2017. “3 Ways Gender Data Could Go Big.” Devex, 21 March 2017. https://www.devex.com/news/3-ways-gender-data-could-go-big-89862. 10 Rogers, Kelli. 2017. 5 This publication may be reused for noncommercial purposes if the source is cited as IFC, a member of the World Bank Group. 11 Rogers, Kelli. 2017. 12 World Bank Group. 2016. “Enhancing Financial Capability and Inclusion in Senegal - A Demand-Side Survey.” Finance & Markets Global Practice, No. ACS18885, June 2016. http://documents.worldbank.org/curated/en/371101467006421447/pdf/ACS18885-WP-P151555-PUBLIC-SENEGAL-Enhancing- Financial-Capability-and-Inclusion-Final-20160615.pdf. 13 Miklyaev, Mikhail, Majid Hashemi, and Melani Schultz. 2017. “Cost Benefit Analysis of Senegal’s Rice Value Chains.” Development Discussion Paper Vol.4. https://cri-world.com/publications/qed_dp_301.pdf. 14 De-Arteaga, Maria and Artur Dubrawski. 2016. “Discovery of Complex Anomalous Patterns of Sexual Violence in El Salvador.” Data for Policy, 2016. https://mariadearteaga.files.wordpress.com/2016/05/discovery-complex-anomalous1.pdf. 15 Everyday Sexism. http://everydaysexism.com/. 16 Africa’s Voices. 2017. “Child Protection and Gender Equality in Somalia.” UNICEF. https://www.africasvoices.org/case-studies/unicef-somalia-child- protection-gender-equality/. 17 Lopes, Claudia and Savita Bailur. 2018. “Gender Equality and Big Data.” UN Women, January 2018. https://www.unglobalpulse.org/sites/default/files/ Gender-equality-and-big-data-en-2018.pdf. 18 Lopes, Claudia and Savita Bailur. 2018. 19 UN. (no year). “Big Data Project Inventory.” Big Data UN Working Group. https://unstats.un.org/bigdata/inventory/?selectID=WB43. 20 Golant, Farah Ramzan. 2017. “Our Vision to Enable 100 Million Girls to Find Their VoiceOnline.” Girl Effect, 18 October 2017. https://www.girleffect. org/stories/our-vision-to-enable-100-million-girls-find-their-voice-online/. 21 UN Global Pulse. 2015. “Measuring Economic Resilience to Natural Disasters with Financial Transaction Data.” Project Series, No. 24. https://www. unglobalpulse.org/projects/using-financial-transaction-data-measure-economic-resilience-natural-disasters. Additional Selected EM Compass Notes Previously Published by IFC Thought Leadership JUNE 2020 NOVEMBER 2019 Note 85: Artificial Intelligence Innovation in Financial Note 75: How Artificial Intelligence is Making Transport Services Safer, Cleaner, More Reliable and Efficient in Emerging Markets MAY 2020 Note 84: Leveraging Inclusive Businesses Models to Support OCTOBER 2019 the Base of the Pyramid during COVID-19 Note 74: Bridging the Trust Gap: Blockchain’s Potential to Note 83: What COVID-19 Means for Digital Infrastructure in Restore Trust in Artificial Intelligence in Support of New Emerging Markets Business Models Note 82: Artificial Intelligence in Agribusiness is Growing in Note 73: Closing the SDG Financing Gap—Trends and Data Emerging Markets SEPTEMBER 2019 APRIL 2020 Note 72: Blended Concessional Finance: The Rise of Note 81: Artificial Intelligence in the Power Sector Returnable Capital Contributions Note 71: Artificial Intelligence: Investment Trends and MARCH 2020 Selected Industry Uses Note 80: Developing Artificial Intelligence Sustainably: Toward a Practical Code of Conduct for Disruptive JULY 2019 Technologies Note 70: How Insurtech Can Close the Protection Gap in Note 80a: IFC Technology Code of Conduct—Progression Emerging Markets Matrix—Public Draft—Addendum to Note 80 JULY 2019 FEBRUARY 2020 Note 69: The Role of Artificial Intelligence in Supporting Note 79: Accelerating Digital Connectivity Through Development in Emerging Markets Infrastructure Sharing JUNE 2019 Note 78: Artificial Intelligence and the Future for Smart Note 68: Basic Business Models for Banks Providing Digital Homes Financial Services in Africa JANUARY 2020 APRIL 2019 Note 77: Creating Domestic Capital Markets in Developing Note 67: The Case for Responsible Investing in Digital Countries: Perspectives from Market Participants Financial Services DECEMBER 2019 MARCH 2019 Note 76: Artificial Intelligence and 5G Mobile Technology Note 66: Blended Concessional Finance: Governance Can Drive Investment Opportunities in Emerging Markets Matters for Impact 6 This publication may be reused for noncommercial purposes if the source is cited as IFC, a member of the World Bank Group. Note 65: Natural Gas and the Clean Energy Transition SEPTEMBER 2017 Note 45: Beyond Fintech: Leveraging Blockchain for More FEBRUARY 2019 Sustainable and Inclusive Supply Chains Note 64: Institutional Investing: A New Investor Forum Note 44: Blockchain in Financial Services in Emerging and Growing Interest in Sustainable Emerging Markets Markets—Part II: Selected Regional Developments Investments Note 43: Blockchain in Financial Services in Emerging JANUARY 2019 Markets—Part I: Current Trends Note 63: Blockchain and Associated Legal Issues for AUGUST 2017 Emerging Markets Note 42: Digital Financial Services: Challenges and Note 62: Service Performance Guarantees for Public Utilities Opportunities for Emerging Market Banks and Beyond—An Innovation with Potential to Attract Investors to Emerging Markets JULY 2017 NOVEMBER 2018 Note 41: Blockchain in Development—Part II: How It Can Impact Emerging Markets Note 61: Using Blockchain to Enable Cleaner, Modern Energy Systems in Emerging Markets Note 40: Blockchain in Development—Part I: A New Mechanism of “Trust?” Note 60: Blended Concessional Finance: Scaling Up Private Investment in Lower-Income Countries Note 39: Technology-Enabled Supply Chain Finance for Small and Medium Enterprises is a Major Growth Opportunity for OCTOBER 2018 Banks Note 59: How a Know-Your-Customer Utility Could Increase MAY 2017 Access to Financial Services in Emerging Markets Note 38: Can Blockchain Technology Address De-Risking in Note 58: Competition Works: Driving Microfinance Emerging Markets? Institutions to Reach Lower-Income People and the Unbanked in Peru APRIL 2017 SEPTEMBER 2018 Note 37: Creating Agricultural Markets: How the Ethiopia Commodity Exchange Connects Farmers and Buyers through Note 57: Blockchain Governance and Regulation as an Partnership and Technology Enabler for Market Creation in Emerging Markets Note 35: Queen Alia International Airport—The Role of IFC in JULY 2018 Facilitating Private Investment in a Large Airport Project Note 56: A Practical Tool to Create Economic Opportunity MARCH 2017 for Low-Income Communities Note 34: How Fintech is Reaching the Poor in Africa and JUNE 2018 Asia: A Start-Up Perspective Note 55: Peru’s Works for Taxes Scheme: An Innovative Note 33: Creating Markets in Turkey’s Power Sector Solution to Accelerate Private Provision of Infrastructure Investment FEBRUARY 2017 Note 32: Private Provision of Education: Opportunities for MAY 2018 Emerging Markets Note 54: Modelo Peru: A Mobile Money Platform Offering Note 31: Improving Emerging Markets Healthcare Through Interoperability Towards Financial Inclusion Private Provision APRIL 2018 JANUARY 2017 Note 52: Crowding-In Capital: How Insurance Companies Note 30: Masala Bond Program—Nurturing A Local Currency Can Expand Access to Finance Bond Market JANUARY 2018 Note 29: Toward a Framework for Assessing Private vs. Note 48: Increased Regulation and De-risking are Impeding Public Investment in Infrastructure Cross-Border Financing in Emerging Markets Note 28: The Importance of Local Capital Markets for Financing Development OCTOBER 2017 Note 47: From Farm to Fork: Private Enterprise Can Reduce DECEMBER 2016 Food Loss Through Climate-Smart Agriculture Note 27: How Banks Can Seize Opportunities in Climate and Note 46: Precision Farming Enables Climate-Smart Green Investment Agribusiness 7 This publication may be reused for noncommercial purposes if the source is cited as IFC, a member of the World Bank Group. IFC 2121 Pennsylvania Avenue, N.W. Washington, D.C. 20433 U.S.A. ifc.org/ThoughtLeadership 8 This publication may be reused for noncommercial purposes if the source is cited as IFC, a member of the World Bank Group.