This research investigates AI-managed household portfolios, finding that large language models recommend undiversified portfolios concentrated in high-momentum, large-cap technology stocks. While returns may exceed market benchmarks, they do not provide abnormal returns when adjusted for risk characteristics. Recommendations are primarily driven by media attention rather than investment skill.

Research demonstrates that Large Language Models exhibit purpose-conditioned bias when informed of downstream tasks. Goal-aware prompting leads to in-sample overfitting and inflated performance before knowledge cutoffs. Results indicate that disclosing objectives compromises neutrality, necessitating the separation of measurement and evaluation in AI-assisted workflows to ensure statistical validity.

This research investigates the demand for explainable AI in high-stakes credit settings. It finds that decision-makers strategically avoid explanations that reveal racial or gender bias to preserve moral wiggle room. Additionally, behavioural biases cause individuals to undervalue explanations even when they complement private information and improve decision accuracy.

This research examines the tradeoff between lender profits and social impact using machine learning across three countries. It demonstrates that algorithmic targeting significantly boosts profit margins in South Africa and the Philippines but may reduce financial inclusion for women and low-income borrowers unless balanced strategies are implemented.

This paper examines Kenya's 2016 interest rate regulation, which capped bank lending rates but exempted the digital platform M-Shwari. Using borrower-level administrative data and a structural model, the authors find that the M-Shwari carve-out preserved credit access for high-risk borrowers, while a uniform cap would have eliminated it entirely.

This paper is the African Chapter of GDF's Global Stablecoin Regulatory Playbook. It examines how global stablecoin regulatory principles can be applied across Africa's diverse markets, addressing reserve management, consumer protection, AML/CFT compliance, and cross-border coordination, while accounting for local financial infrastructure, dollarisation risks, and varying supervisory capacity.

This report examines the impact of digital innovation on financial health. It outlines opportunities in payments, credit, savings, and insurance, whilst highlighting emerging risks such as fraud, overindebtedness, and ill-suited investments. The authors propose policy responses to enhance regulatory frameworks and promote responsible digitalisation in financial services.

This report proposes a rigorous framework for third-party auditing of frontier AI systems to verify safety and security claims. Addressing the opacity of current self-assessments, it advocates for structured AI Assurance Levels, deep access to non-public information, and continuous monitoring to enable confident deployment and standardisation across the industry.

This report explores how alternative data and artificial intelligence are redefining credit scoring to enhance financial inclusion for women and underserved borrowers. It analyses market trends, evaluates the risks of algorithmic bias, and provides actionable recommendations to scale responsible, inclusive credit access across emerging markets.

The paper analyses the European Commission’s proposed “EU Inc.” framework, a harmonised digital-first company structure for EU start-ups and scale-ups. It assesses governance, financing, codetermination, digital registration and cross-border legal integration within existing EU and national company law frameworks.

This report outlines 2026 financial crime and regulatory risks in the GCC, focusing on AI-enabled fraud, digital assets, cybercrime, beneficial ownership, supply chains, sanctions, and tougher AML/CFT oversight linked to upcoming FATF evaluations and recent legal reforms in the UAE, Bahrain and Saudi Arabia.

This IPBES–IPCC workshop report examines interlinkages between biodiversity, climate change and society, identifying synergies, trade-offs and risks. It assesses mitigation and adaptation impacts on ecosystems and people, and outlines integrated, nature-based solutions to inform climate and biodiversity policy and governance.

Linux Foundation is a global non-profit that enables open source collaboration at scale. It hosts and supports critical projects across cloud, Linux, security and AI. Activities include governance, research, training, certification and events, helping organisations build, adopt and sustain open source technologies worldwide for industry, public sector and developer communities.

The report outlines a framework for a Responsible Digital Finance Ecosystem, urging holistic, collaborative consumer protection amid rising digital finance risks. It defines ecosystem actors and four pillars—customer centricity, collaboration, capability, and commitment—to strengthen regulation, improve outcomes, and reduce harms in rapidly evolving digital financial services.

MDPI (Multidisciplinary Digital Publishing Institute) is a Swiss-based publisher of open access, peer-reviewed journals, established in 1996. MDPI publishes over 470 academic journals across science, technology and medicine, with authors covering article processing charges to enable unrestricted global access.

LSEG (London Stock Exchange Group) is a global financial markets infrastructure and data provider. It delivers market-data, analytics, news and index products to over 44,000 customers in more than 170 countries. LSEG’s services cover capital markets, post-trade operations, risk management and information services.