A Decade of Blended Finance in India and What Lies Ahead

This report from Blended Finance India reviews the progress and future outlook of blended finance in India over the past decade. It likely analyses key trends, policy developments, and the impact of blended finance instruments on various sectors. The authors probably identify successes, challenges, and lessons learned, offering recommendations for accelerating the adoption and effectiveness of blended finance. The paper aims to provide a comprehensive narrative on India’s journey in blended finance, guiding stakeholders toward more strategic and impactful interventions to address the country’s development needs.

Data Mining Approach to Minimise Child Malnutrition in Developing Countries

This study proposes a data mining framework to identify factors contributing to child malnutrition in developing countries. It explores how data-driven insights can aid policy design and intervention planning. Using machine learning algorithms, the authors analyse demographic, socio-economic, and nutritional datasets to detect high-risk groups and actionable patterns. The approach supports evidence-based policy making to combat child malnutrition effectively.

Gis for Effective Monitoring of Orchards

This case study from Geospatial World discusses how Geographic Information Systems (GIS) have been implemented to monitor orchards effectively. It showcases how spatial data, mapping, and real-time analysis are used to track crop health, improve productivity, and manage agricultural resources more efficiently. The solution enables precision farming by integrating satellite imagery and GIS analytics to detect anomalies and optimise resource use. This innovation highlights the impact of geospatial technology in enhancing agricultural sustainability and supporting data-informed decisions at scale for rural development.

Data Science and Advanced Analytics are Transforming the Water Industry

This blog examines how data science and advanced analytics are revolutionising the water industry. It discusses technologies such as predictive modelling, real-time monitoring, and AI-powered optimisation used to improve infrastructure efficiency, reduce operational costs, and ensure regulatory compliance. The article presents successful case studies demonstrating how utilities have leveraged data to enhance water resource management.

Finance in Common Summit November 11-12, 2020 Paris, France

This event report summarizes the Finance in Common Summit, the first global meeting of Public Development Banks (PDBs), held in Paris. The summit focused on how PDBs can influence the global financial system to better protect the planet and societies. Key discussions centered on strengthening commitments to the Paris Agreement goals, mobilizing climate finance, and addressing social issues in the context of COVID-19. The report highlights the International Development Finance Club’s (IDFC) efforts to operationalise Paris alignment through tools, a Climate Facility, and strategic partnerships, underscoring the collective engagement of PDBs in sustainable development.

Can Data Science Help Develop Clean and Renewable Energy?

This NREL insight report discusses how data science is driving innovation in clean and renewable energy. It describes platforms like the Open Energy Data Initiative, which aggregates terabytes of energy metrics into accessible ‘data lakes’ to support research, forecasting, and policy planning. NREL’s Insight Center applies advanced computing—including generative ML models—to simulate future grid scenarios, improve material discovery, and optimize energy storage. The piece emphasizes cross-sector collaboration, open data standards, and high-performance computing. It argues that integrating data analytics is critical for accelerating clean energy deployment, resilience, and net-zero strategies worldwide.

Environmental and Social Framework

This document outlines the Asian Infrastructure Investment Bank’s (AIIB) Environmental and Social Framework (ESF), which serves as a guiding policy for all its investment operations. The framework sets out the Bank’s commitments and requirements for identifying, assessing, and managing environmental and social risks and impacts. It emphasizes due diligence, stakeholder engagement, and robust management systems to ensure sustainable outcomes. The ESF aims to integrate environmental protection and social considerations into infrastructure projects, promoting responsible development and contributing to positive and lasting benefits for affected communities and the environment.

Data Science and Analytics for Sustainable Development

This article discusses the role of data science and analytics in achieving Sustainable Development Goals (SDGs) by enabling better resource planning, targeted intervention, and impact tracking. It highlights how data-driven approaches improve decision-making across sectors such as health, education, agriculture, and energy. The piece outlines the importance of interdisciplinary collaboration, technological adoption, and institutional capacity-building to scale outcomes. By examining real-world applications, it stresses the need for inclusive, context-sensitive, and evidence-based solutions to address complex developmental challenges.

Enhancing Commitment Towards Sustainable Financing, India Exim Bank Sets Up Its Esg Framework

This press release from India Exim Bank announces the establishment of its Environmental, Social, and Governance (ESG) Framework, demonstrating an enhanced commitment towards sustainable financing. The framework aims to integrate ESG considerations into the bank’s operations and financing activities, promoting responsible and impactful investments. It highlights the bank’s efforts to align with global best practices in sustainable finance and to contribute to positive environmental and social outcomes. This initiative reflects a strategic move to embed sustainability deeply within its financial practices and enhance its overall impact.

Can Computer and Data Science Help Accelerate Sustainable Agriculture?

This Syngenta Group blog explores the transformative potential of computer science and data analytics in sustainable agriculture. It reports on advanced tools—soil sensors, satellite imagery, and AI-powered models—that enable precision guidance on crop selection, irrigation, and pest control. The article highlights Syngenta’s ‘soil intelligence’ initiative in U.S. and global pilot regions, showing improvements in yield, soil health, and resource efficiency. It addresses ecosystem resilience, climate adaptation, and farmer empowerment. The piece stresses that integrating technology with agronomic expertise can deliver regenerative farming practices, scalable impact, and food-security benefits globally.
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