Fresh Ideas About Business in Emerging Markets

The COVID-19 pandemic and the resulting economic shutdown have severely depressed electricity demand across the globe, with acute consequences for the revenues and financial health of utilities, as well as smaller providers of utility services and off-grid companies. In many places, utility service providers also must manage the inability of consumers to pay for their services. Government support has been forthcoming, but utilities need to work closely with policymakers to ensure that programs are carefully designed in order to maintain ongoing system reforms, competitiveness, and affordability, and avoid long-lasting market disruptions. These support measures should avoid redundancy among sectors and ensure that resources are efficiently allocated and that welfare improvements are fairly distributed across the country in a sustainable manner. Investors must also understand changes to utilities’ finances and should work to support further reforms.

This report explores the latest AI applications and trends in emerging markets and includes several examples of how AI is expanding opportunities and contributing to the achievement of the Sustainable Development Goals. It also sheds light on how investors, clients, and governments can harness its full potential while minimizing its risks—when managed effectively and with safeguards in place, AI can facilitate private investment to reduce poverty and improve lives at a pace inconceivable only a decade ago.

Social bonds have become an increasingly popular fixed-income product since the Social Bond Principles were published in 2017, and their growth and popularity have accelerated in recent months due to the onset of the COVID-19 pandemic and the resulting need for new funding avenues to address the unforeseen economic and social disruptions. Since the outbreak of the crisis, global issuances of social bonds have risen considerably, and an increasing number of market participants have turned to IFC, a prolific and experienced issuer of social bonds, for advice on how to set up Social Bond Programs and Social Bond Frameworks. The hope now is that social bonds can become a significant method for financing projects that mitigate the socioeconomic impact of the current health crisis, and that the growing use of and interest in these bonds can be sustained post-crisis.

This note highlights the East Asian lessons that African nations, and Ethiopia in particular, are putting to use. These include focusing on competitiveness in select industries, acquiring know-how from global leaders, seeking foreign partners and investment, and developing a national strategy to create the industries of the future. The application of these lessons is also of interest to private investors, as it can allow them to identify the economies utilizing Economic Fitness analyses and thus offer opportunities for growth and investment.

As advances in machine learning, computer vision, and robotics help manufacturers around the world improve their processes and produce new and more complex products, artificial intelligence (AI) is becoming an integral tool of modern manufacturing, and one that is increasingly important to the industry’s future. By combining large volumes of data with the computing power to simulate human thinking, AI is increasing the efficiency, capacity, and complexity of factory floors, and is introducing robotics, the Internet of Things, and other cutting-edge innovations to manufacturing value chains across the globe.

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.

Artificial intelligence technologies are permeating financial services sectors around the world. The application of these technologies in emerging markets allows financial service providers to further automate their business processes and to leverage new and big data sources to overcome obstacles— including the high cost of serving rural and low-income customers and establishing customer identity and creditworthiness—that prevent the delivery of financial services to many consumers. Realizing financial inclusion benefits through the adoption of artificial intelligence relies on its responsible adoption by firms, on competitive market settings, and on continued investment in the necessary infrastructure.

The COVID-19 crisis is expected to roll back some of the progress made against global poverty over the last two decades, with the greatest impact on individuals at the base of the economic pyramid. Inclusive businesses that expand access to goods, services, and livelihoods for these individuals are responding to the crisis by reorienting and adapting their inclusive business models and operations. This note highlights seven actions that companies are taking to address needs at the base of the pyramid. We present their actions here as examples of what other businesses could do in response to the needs of those at the base of the pyramid.

The COVID-19 pandemic shows that digital connectivity is critical to societal resilience and business continuity in times of crisis. For digital infrastructure providers in emerging markets, higher demand for connectivity may be counterbalanced by a series of negative shocks. These could affect broadband operators and smaller companies, leading to less competition, limited availability of open-access broadband infrastructure, and reduced technological innovation. However, the perceived value of digital connectivity is likely to rise, creating opportunities to implement policy reforms to accelerate the rollout of 4G and 5G. Digital infrastructure companies, however, may accelerate their migration toward diversified business models. Against a background of funding withdrawal from emerging markets, financing for smaller or independent companies in the poorest economies may require substantial support from development finance institutions to preserve competition, improve resilience, and pr

Business models utilizing artificial intelligence can help meet rising global demand for food and support a more inclusive and sustainable food system by: (1) enhancing the resilience of farming methods; (2) reducing the cost of quality inputs and services to underserved farmers; and (3) improving market access to facilitate smallholder farmer integration into regional and global supply chains. Although nascent in emerging economies, applications for artificial intelligence in agribusiness will proliferate as farmers’ access to the Internet and adoption of smart devices increases across low-income countries.

The energy sector worldwide faces growing challenges related to rising demand, efficiency, changing supply and demand patterns, and a lack of analytics needed for optimal management. These challenges are more acute in emerging market nations. Efficiency issues are particularly problematic, as the prevalence of informal connections to the power grid means a large amount of power is neither measured nor billed, resulting in losses as well as greater CO2 emissions, as consumers have little incentive to rationally use energy they don’t pay for. The power sector in developed nations has already begun to use artificial intelligence and related technologies that allow for communication between smart grids, smart meters, and Internet of Things devices. These technologies can help improve power management, efficiency, and transparency, and increase the use of renewable energy sources.

The adoption and diffusion of artificial intelligence and other disruptive technologies will play an important role in market creation and growth. Development finance institutions have a role to play in leveraging their investments to ensure that these technologies sustain both growth and development objectives. To this end, the authors propose adoption of a Technology Code of Conduct as a framework, supported by a set of practical tools for its operationalization, to assist IFC’s clients engaged in technology intensive projects.

The Progression Matrix is a tool that helps companies adopt the Technology Code of Conduct—a framework designed for IFC clients engaged in technology-intensive projects. In this addendum to Note 80, the Matrix identifies technical and business practices that help companies put principles of sustainable technology into practice in a way consistent with their stage of financing and maturity, including emerging, later-stage, and mature companies.

Digital connectivity has enormous potential to support development. Yet today some four billion people in emerging economies remain offline, partly due to a lack of affordable Internet access. Sharing infrastructure among operators and across sectors is a potential solution. It can accelerate digital connectivity at lower cost, especially in the least developed markets where returns to investment can be limited. It can also reduce investment costs and operating expenses for investors and operators, and increase their balance sheet sustainability. Sharing models can also benefit consumers by increasing competition, lowering prices, and raising service quality. The private sector has already embraced this model; further expansion requires targeted policies that promote competition and facilitate sharing.

Population growth and urbanization in emerging markets will mean expanding cities and rising demand for new housing in urban areas around the world. These trends represent an enormous opportunity to design, build, and operate the homes of tomorrow in intelligent ways that minimize energy consumption and carbon emissions, lower building and homeowner costs. Artificial intelligence will play a pivotal role in this effort by using data—including grid data, smart meter data, weather data, and energy use information—to study and improve building performance, optimize resource consumption, and increase comfort and cost efficiency for residents. AI will also analyze data collected from multiple buildings to improve building design and construction and inform future policy making related to construction and urban planning.

Domestic capital markets that are deep, efficient, and well-regulated can create access to long-term, local-currency finance. Interviews with market participants reveal four important findings. First, there are two distinct phases of capital market development, an embryonic phase in which the government is predominant and a mature phase in which the capital market starts to serve the private sector. Second, capital market development requires continuous monitoring and policy interventions due to changing market stages. Third, while capital markets are a crucial source of large volume, long-term local currency finance, they often fail smaller countries and companies. Finally, as the capital market develops, intangible or “soft” factors become more important.

The intersection of artificial intelligence and 5G mobile technology has enormous potential to deliver dramatic improvements in productivity, efficiency, and cost across business sectors and broader society, delivering innovative products and services not previously possible. Though mainstream applications that combine AI and 5G have yet to emerge, key emerging markets sectors such as agribusiness, healthcare and education will be transformed by the combination of AI and 5G. While many mobile operators remain focused on recouping their investments in previous network standards, there is a growing interest in 5G networks globally.

Transport in emerging markets often faces acute challenges due to poor infrastructure, growing populations, urbanization, and in some regions rising prosperity, which increases vehicle traffic, cargo volumes, and pollution. Artificial intelligence offers new solutions to these challenges by making market entry easier and allowing countries to reach underserved populations, creating markets and private sector investment opportunities associated with them.

Rapid increases in computing power and data generation have turned artificial intelligence, blockchain, and the Internet of Things into potent technologies that are rapidly gaining use in many areas of society and commerce, with significant potential benefits for economic growth and development. These innovative technologies face multiple obstacles to implementation and—particularly in the case of AI—a general wariness of their potential implications for human society. Fortunately, an integrated implementation of the three technologies may be a solution that can restore human trust in AI and blockchain applications, resulting in new business models that deliver data security and privacy, efficiency, and inclusion along with their many other benefits.

How big is the financing gap to achieve the 2030 Sustainable Development Goals (SDGs)? Can private capital fill the gap? This note provides an updated overview of estimates of SDG financing in low- and middle-income countries and gives an analytical and data-based foundation for discussion. Based on a review of recent studies, as well as IFC’s own calculations of cross-border flow trends, the note documents the ongoing and significant SDG financing gap. Raising taxes to expand public spending is an option for many middle-income countries to fill the gap, but it will be insufficient for low-income countries. Private financing, especially of infrastructure, can also contribute to bridging the gap, but it will depend on the availability of investable projects. Capital market development and improved domestic financial systems can help intermediate more private capital into available investment opportunities.

In new and challenging markets, blended concessional finance—the combining of concessional funds with other types of finance, on commercial terms—is increasingly used to mobilize capital and accelerate high impact private sector investments. However, a relatively new approach for the provision of concessional capital for use by development finance institutions is emerging—the “returnable capital” model. With this new model, principal, interest, and other amounts are repaid to the original provider of funds (usually a government) on a regular basis. Because this can reduce the impact on donor government budgets, more government funds could become available for collaboration with the private sector. This note explores the effects of this new model on incentives, accounting, resource management, and reporting.

The global race to fund, develop, and acquire artificial intelligence (AI) technologies and start-ups is intensifying, with commercial uses for AI proliferating in advanced and emerging economies alike. AI could increase GDP growth in both advanced countries and emerging markets. In healthcare, diagnosis and drug discovery will benefit enormously from AI. In manufacturing, AI can help design better products in terms of functionality, quality, and cost, and improve predictive maintenance. The potential impact of AI on transportation and logistics goes far beyond automation and road safety to span the entire logistics chain. Yet with the exceptions of China and India, emerging markets have received only a modest share of global investment in this advanced technology, despite the fact that they may benefit more from AI implementation than advanced economies.

Insurance technology, better known as Insurtech, is a rapidly growing industry that is beginning to disrupt traditional insurance provision in advanced and emerging economies alike, and is creating opportunities and challenges for incumbents, start-ups, and investors. The opportunity offered by insurtech is particularly significant in emerging markets, where a large “protection gap” exists due to low insurance penetration. This has major development implications due to the fact that economic growth and insurance penetration are closely intertwined. Technology and new business models are necessary to close the protection gap in these markets, and companies will need to be able to innovate—either internally, by partnerships, or by investing—to seize the opportunity.

Artificial Intelligence (AI) has enormous potential to augment human intelligence and radically alter how we access products and services, gather information, make products, and interact. In emerging markets, AI offers an opportunity to lower costs and barriers to entry for businesses and deliver innovative business models that can leapfrog traditional solutions and reach the underserved. Harnessing the power of AI is becoming increasingly important to economic development in many nations, and the goals of ending poverty and boosting shared prosperity may become dependent on it. Private sector solutions can play a major role here; to scale new business models, develop new ways to deliver services, and increase local markets’ competitiveness.

The rapid growth of credit over the last two decades has led to increased levels of non-performing loans across the globe. This can reduce lending and hamper economic recovery, creating a vicious circle that can be difficult to break. However, robust distressed assets markets can interrupt this loop, allowing for a return to financial stability and economic growth. IFC, through its Distressed Asset Recovery Program (DARP), is taking the lead in developing strong distressed assets markets in emerging economies.