The report explores how artificial intelligence (AI) and machine learning (ML) can address challenges in global pension systems. It highlights AI's potential to enhance governance, personalisation, fraud prevention, and investment strategies while emphasising ethical implementation and data privacy considerations to optimise retirement outcomes and ensure system sustainability.

The report explores the potential of blockchain technology in financing infrastructure projects. It evaluates blockchain's capabilities in enhancing efficiency, transparency, and accessibility in infrastructure tokenisation, while addressing challenges like regulatory constraints, market adoption, and technical barriers. The findings highlight both opportunities and limitations for integrating blockchain into infrastructure financing.

The report reviews blockchain's role in sustainability, analysing 10,188 studies. It highlights blockchain's potential in supply chain management, energy systems, and IoT-based solutions like smart cities. However, gaps persist in aligning blockchain applications with global ESG regulations and carbon trading mechanisms. Recommendations aim to improve blockchain's utility in achieving net-zero goals.

The report explores blockchain technology's relevance to responsible investment, highlighting its potential to enhance transparency, automate processes, and improve ESG data tracking. It discusses blockchain's implications for shareholder voting, decentralised systems, financial inclusivity, and sustainability. Practical challenges, including regulation, technical integration, and energy use, are also addressed. .

The report discusses the rapid adoption and integration of artificial intelligence (AI) in the financial sector, driven by advancements in technology and increasing operational efficiency. Key risks include dependencies on third-party providers, market correlations, and cyber vulnerabilities. Generative AI's accessibility could amplify systemic risks, necessitating enhanced regulatory frameworks, vigilant monitoring, and robust governance to ensure financial stability amid evolving AI technologies.

The report outlines a pattern-oriented engineering approach for responsible AI in financial services. It identifies challenges in scaling responsible AI, introduces a Responsible AI Pattern Catalogue for addressing lifecycle risks, and provides case studies on chatbot development. The study underscores governance, process, and product strategies to operationalise responsible AI principles effectively.

This tool measures the environmental impact of economic activity, company, or sector, to deliver a net contribution value on -100% to +100% scale, using physical data from across the value chain. It can be applied at company, portfolio, index, product/source levels. Includes qualitative and quantitative criteria on biodiversity.

Powered by data from Trase Earth, Forest IQ has been developed to support banks and investors assess and manage their exposure to deforestation risk. Forest IQ provides market leading data about corporate performance on deforestation impacts, land conversion, and natural ecosystem and human rights abuses. Trase Earth offers open source data that is free to download.

The hub hosts a collection of tools and guidance to help financial institutions harmonise environmental and social impact monitoring for sustainable land use finance.

EXIOBASE is a global, detailed Multi-Regional Environmentally Extended Supply-Use Table (MR-SUT) and Input-Output Table (MR-IOT). It was developed by harmonising and detailing supply-use tables for a large number of countries, estimating emissions and resource extractions by industry.

The report examines the impact of generative AI on American jobs, noting significant disruption in both cognitive and nonroutine tasks, particularly in middle- and high-wage sectors. It highlights the need for policies that engage workers in AI’s deployment, enhance worker rights, and ensure AI-driven advancements benefit workers while minimising risks.

This handbook provides a comprehensive overview of artificial intelligence (AI) and big data applications in investments. It covers topics such as machine learning, natural language processing, trading algorithms, and AI-driven customer service. Aimed at finance professionals, it offers insights into practical use cases, challenges, and evolving trends in AI adoption, making it a valuable resource for those navigating the integration of these technologies in investment strategies.

KnowTheChain’s benchmark evaluates corporate efforts to address forced labour in global supply chains. It assesses companies across sectors using indicators such as worker rights, transparency, and risk management. This tool helps finance professionals and investors identify risks and drive improvements in corporate labour practices, promoting ethical and responsible investment decisions.

The report explores the energy challenges posed by AI adoption, highlighting concerns among IT managers about increased energy consumption and uncertainty regarding its impact on sustainability. The research underscores the need for enhanced energy efficiency and green energy solutions to meet ESG goals without hindering AI deployment.

This guide provides essential guidelines for companies and investors to enhance human rights due diligence, particularly in supply chains. It emphasises transparency, risk assessment, and responsible purchasing practices to combat forced labour. The guide also offers practical examples and benchmarks, helping stakeholders align with global standards and improve corporate disclosures.

The Natural Capital Protocol provides a step-by-step guide for businesses to measure, value, and integrate natural capital into their operations. Divided into 9 stages, this comprehensive guide offers a practical approach to assess material risks and opportunities, communicate with stakeholders, and make informed decisions towards sustainable business practices.