July 2026

How Rational Is AI Investment Advice? Risk-Return Relevance in Artificial Intelligence (AI) Investments

By Nanying Lin, Oscar Gilbert & Tianxiang Chu Textbook finance theories indicate that investors demand risk premia from risky assets as compensation for risk and for hedging against future unfavorable economic states. We design a comprehensive study to examine whether investment advice generated by artificial intelligence (AI) reflects a coherent risk–return pattern in investment decision-making. We find that AI advises investors to increase stock investments when return increases and reduce stock allocations when stock volatility increases. However, AI ignores the...

Pension Income and Post-Retirement Labor Supply

By Fabian Kindermann, Carla Krolage, Sebastian Kunz, Manuel Pannier & Karoline Ströhlein This paper provides causal evidence on how pension income affects labor supply after retirement. We exploit the introduction of the German Earned Income Pension Credit (Grundrente), which permanently increased pension income for retirees with long contribution histories and comparatively low lifetime earnings. The reform generates exogenous variation in non-labor income without creating additional labor supply distortions, allowing us to isolate pure income effects. Using administrative data covering the...

Artificial Intelligence in Elderly Care: Navigating Ethical and Responsible AI Adoption for Seniors

By David Mhlanga This paper delves into the critical intersection of ageing and the rapidly evolving field of artificial intelligence (AI). This exploration is anchored in the recognition of the unique potential that AI holds for enhancing the lives of seniors, while also acknowledging the complex ethical and practical challenges that accompany its adoption in elder care. The paper comprehensively examines how AI can revolutionize healthcare, assistive technologies, and social engagement for the elderly, offering solutions that promise increased independence,...

June 2026

Insights and Analysis: The AI Revolution

By Pension Trusts Enhanced Data Management and Predictive Analytics Central to the operations of DB pensions is the handling of extensive and diverse data sets. AI can significantly improve the way data is managed through advanced data processing abilities. With machine learning algorithms, there's the potential to dissect decades of pension data. This could help identify underlying trends, enhance the valuation of long-term liabilities and fine-tune outcomes. Conventional actuarial models in Asset Liability Management (ALM) are based on time-tested statistical methods. While...

Avoiding the ‘pink pound’ blind spot

By Scottish Widows  While Pride celebrations carried on around the UK, the reality is that ‘pink finances’ remain in dire straits. It was a common trope not that long ago that this cohort of society was more likely to be more affluent than average. But the reality is very different. In fact, the challenges facing LGBTQ+ people are vast, and this group is much more likely to have a range of different vulnerabilities. To ensure that they continue to deliver the...

What Do Prospective Teachers Retirees’ Fear about Retirement?

By Jaquiline Amani This qualitative study explored prospective teacher retirees’ perceived fears about retirement and identified key drivers of retirement anxiety. Data were collected through focus group discussions with 22 teachers from two regions of Tanzania. The participants were purposively selected from public schools and had ten years or less remaining before reaching voluntary or mandatory retirement age. Thematic analysis revealed that teachers’ fear of retirement was shaped by multiple, interconnected factors, including anticipated social exclusion, income reduction and financial...

The financial well-being of retired professional athletes: debunking the myth about financial irresponsibility

By Grant Laschowski & Norm O'Reilly This research aims to investigate the financial well-being (FWB) of retired male athletes in major professional North American team sports. Framed around Kempson’s (2017) FWB Model, the aim of this research is (1) to identify the key drivers that influence how retired athletes feel about their current financial situations and (2) to assess these findings in the context of how external constituents view the FWB of these athletes. The research addressed two questions: What...

LGBTQ+ Labor Market Outcomes

By Travis Campbell & Yana Van Der Meulen Rodgers The emerging field of LGBTQ+ economics has convincingly demonstrated that LGBTQ+ individuals face distinct labor market disparities. This chapter provides an overview of their unfavorable labor market outcomes and then focuses on several specific issues for transgender workers. Previous studies show that gender-affirming care can improve mental health, whereas conversion therapy, which denies an individual's gender identity, damages mental health. An unexplored question is whether these mental health effects extend to...

May 2026

The Duty to Explain: Fiduciary Intelligibility Under ERISA

By Ian Edwards This Essay examines whether the Employee Retirement Income Security Act of 1974 (“ERISA”) contains an emerging principle of fiduciary intelligibility within its participant disclosure framework. ERISA requires Summary Plan Descriptions (“SPDs”) to be written in a manner “calculated to be understood by the average plan participant.” While modern pension disclosure has become increasingly sophisticated and financially technical, this Essay argues that administrative and financial disclosure are not necessarily equivalent to fiduciary intelligibility. The Essay does not propose a...

Zero-Trust Architecture for Multi-Tenant SaaS Platforms on AWS:A Practitioner Framework for Authentication, Authorisation, and KYC in Regulated Financial Services

By Alan Terriaga Multi-tenant Software-as-a-Service (SaaS) platforms operating in regulated financial services face a unique intersection of security, compliance, and operational challenges that traditional perimeter-based architectures cannot adequately address. This paper presents a practitioner framework for implementing Zero-Trust Architecture (ZTA) across all layers of an AWS-hosted SaaS application, with particular focus on the authentication, authorisation, and Know Your Customer (KYC) verification pipelines that underpin financial compliance obligations. Drawing on direct engineering delivery experience leading IAM systems in regulated multi-tenant environments, we...