SARAH GADD | Chief Data Officer, Bank Julius Baer

Data governance has come a long way from its inception in the 1980s, transitioning from a necessary overhead to a vital
business capability enabling intelligence at scale. This article discusses the data governance journey to data governance 3.0, the role data products can play in risk-managed business self-service with a future view, and the lessons we can learn that will help move AI governance from infancy to value enabler at scale.


ROSS P. BUCKLEY | Australian Research Council Laureate Fellow and Scientia Professor, Faculty of Law and Justice, UNSW Sydney
DOUGLAS W. ARNER | Kerry Holdings Professor in Law and Associate Director, HKU-Standard Chartered FinTech Academy, University of Hong Kong
DIRK A. ZETZSCHE | ADA Chair in Financial Law, University of Luxembourg
LUCIEN J. VAN ROMBURG | Postdoctoral Research Fellow, UNSW Sydney

In our new book, FinTech: finance, technology, and regulation - Buckley et al. (2024), based on analysis of experiences with the integration of new technologies into finance and of digital financial transformation around with world, we present strategies for policymakers and regulators seeking to build FinTech and innovation ecosystems, to support digital financial transformation and inclusive, resilient, and sustainable digital finance. 

This strategy comprises three levels. First, we focus on the central role of digital public infrastructure and digital financial infrastructure, based on a four-pillar strategy, which includes: (i) digital ID and e-KYC systems; (ii) open, interoperable electronic payment systems; (iii) electronic government provision of services; and (iv) enabling new activities, business, and wider development. Second, we set out seven elements that encompass appropriate regulatory approaches to support digital finance. Finally, we highlight the role of the wider ecosystem, focusing in particular on data strategies and support for research and innovation. 

This strategy is central to balancing the risks and opportunities of digital finance, FinTech, and innovation to contribute meaningfully to the advancement of inclusive sustainable development.


ADAM WILLIAM CHALMERS | Senior Lecturer (Associate Professor) in Politics and International Relations, University of Edinburgh
ROBYN KLINGLER-VIDRA | Reader (Associate Professor) in Entrepreneurship and Sustainability, King’s Business School
DAVID AIKMAN | Professor of Finance and Director of the Qatar Centre for Global Banking and Finance, King’s Business School
KARLYGASH KURALBAYEVA | Senior Lecturer in Economics, School of Social Science and Public Policy, King’s College London
TIMOTHY FOREMAN | Research Scholar, International Institute for Applied Systems Analysis (IIASA)

This article offers insights into what sustainable finance means and how it is addressed in the public policy context using a subset of the Carrots & Sticks dataset that comprises 1,070 sustainable finance policies. The study reveals the financial services sectors targeted, who is governing, and how binding sustainable finance policies are. 

Additionally, the study explores whether policymakers and standard-setters concentrate their efforts on recommending positive action or establishing binding rules. The findings help to advance a shared understanding of the governance of sustainable finance in the context of public policymaking.


BEN MENG | Chairman, Asia Pacific, Franklin Templeton
ANNE SIMPSON | Global Head of Sustainability, Franklin Templeton

Many government policies – both carrots and sticks – are driving the global transition to greener energy systems. In this article, we compare regulatory sticks, like carbon pricing, with carrots like feed-in tariffs that subsidized solar renewables in countries like Germany. 

We reviewed carbon pricing across the globe and discuss why higher prices remain challenging to implement politically. We also challenge the view that government subsidies are wasteful and discuss the steps taken by different countries to lower emissions. We conclude with an optimistic outlook of the U.S. government’s new industrial policy and note a new record in global investments in low-carbon technologies. 

That said, governments in China, the E.U., and the U.S. are deploying carrots and sticks at markedly different speeds and intensity. Looking ahead, global security analysts seeking to generate alpha will need to integrate top-down subsidies into bottom-up security analysis to uncover risks and opportunities.


JOSÉ PARRA-MOYANO | Professor of Digital Strategy, IMD

Data cooperatives, entities that allow individuals to pool together their personal data to gain collective bargaining power and enable them to monetize their data, are emerging. This article describes the economic mechanisms that motivate the
emergence of data cooperatives and analyzes the challenges and opportunities that the existence of these cooperatives implies for business leaders.


MAURIZIO MARCON | Strategy Lead, Analytics and AI Products, Group Data and Intelligence, UniCredit

The recent wave of enthusiasm for artificial intelligence, accentuated by the advent of ChatGPT 3.5, has resulted in technology firms and businesses racing to harness the potential of increasingly sophisticated AI systems. Yet, the pivotal element for maximizing the benefits of these technologies, namely human engagement, is often overlooked. 

To navigate the complexities and opportunities of AI, companies must prioritize “human/AI augmentation” strategies. These strategies should focus on fostering AI awareness, education, and culture to empower employees with the knowledge to leverage AI effectively. Additionally, adopting innovative organizational change management approaches encourages AI experimentation, enabling the discovery of relevant use-cases. Crucially, pragmatic reasoning should try to reimagine the roles within an AI-empowered workforce, actively shaping the future instead of adopting a “wait and see” attitude.

Establishing dedicated teams at the crossroads of AI’s potential and human considerations is essential. By implementing comprehensive, people-centric plans, organizations can unlock AI’s full potential, ensuring a harmonious integration that benefits not just the business but society at large. This holistic approach will pave the way for enhanced competitiveness and profitability in the AI-driven future.


NICK REESE | Cofounder and COO, Frontier Foundry Corporation

Convergence is when two or more separate technologies are paired together to create a capability that is greater than the original technologies individually. The additional value of the converged system itself now opens new applications as well potentially new challenges. 

As policy conversations around emerging technology implications grow, the importance of considering convergence is paramount for effective and trustworthy implementation of technologies in municipal spaces. A connected community is not a technology but a convergence concept that touches millions of citizens, their privacy, and the critical infrastructure on which each of them depend. 

As with all examples of convergence, there are implications beyond the sum of their parts and connected communities is no exception. Officials and individual users are familiar with the implications of connected technologies on individual privacy but the concept of municipal, community, or regional privacy is new. The aggregated data of an entire community or region take the concept of privacy to the homeland security level, driving increased need for effective policies and controls to ensure the safety and security of citizens living inside these architectures. 

This article explores specific challenges for the implementation of municipal IoT and introduces the concept of privacy at the municipal, community, and regional levels.


XAVIER LABRECQUE ST-VINCENT | Associate Partner, Capco
VARENYA PRASAD | Principal Consultant, Capco

In an artificial intelligence enabled organization, traditional data governance practices face challenges due to the complexity of AI algorithms, utilization of unstructured data, dynamic data transformations, integration with external data sources, and the lack of interpretability in AI models. 

To overcome these challenges, financial institutions can deploy strategies to increase transparency, refine metadata for unstructured data, and foster collaboration. Furthermore, data ownership and stewardship roles demand evolution in the AI-driven landscape. Ownership now encompasses AI models, algorithms, and insights. 

To address the needs of stakeholders and ensure responsible AI usage, collaboration, technical expertise, and a focus on governance and compliance become crucial. By adapting their data governance frameworks to accommodate the unique challenges presented by AI, financial institutions can maximize the value of AI technologies while maintaining data quality and trustworthiness. 

This transformation in data governance is essential for financial institutions to capitalize on the benefits of AI and maintain a competitive edge in the industry.


ANNE LAFARRE | Associate Professor in Corporate Law and Corporate Governance, Tilburg Law School

This article explores the divergent regulatory, political, and societal trends in Europe and the U.S. regarding the environmental, social, and governance rights and duties of institutional investors. While the SEC in the U.S. has demonstrated a greater focus on stricter ESG disclosure rules, political debates persist, reducing ESG discussions to mere ideology.

In contrast, Europe exhibits a significant surge in sustainable finance and corporate governance, emphasizing transparency obligations outlined in regulatory initiatives like the SFDR. Examining the tools available to institutional investors, this article delves into the disparities in duties imposed on them in the U.S. and Europe and scrutinizes the voice tools they employ for promoting ESG goals as active owners, with a particular focus on shareholder sustainability proposals.

In conclusion, this article highlights the need for a more harmonized and effective approach to sustainable investment. It advocates aligning European aspirations for sustainable capital allocation in the member states with increased emphasis on sustainability voice, potentially through a forthcoming new Shareholder Rights Directive (SRD III).


BRIAN CLARK | Rensselaer Polytechnic Institute
MAJEED SIMAAN | Stevens Institute of Technology
AKHTAR SIDDIQUE | Office of the Comptroller of the Currency

Machine learning methods, the foundation of much of artificial intelligence, are now widely used in data analysis and model-building across a variety of disciplines. These techniques have also become the underpinnings of many of the business intelligence (BI) analytics that are being widely deployed across a wide range of industries. 

In this article, we focus on some elements of inference around analytics possible in machine learning, contrasting them with how applied econometricians traditionally approached inference. We do this in the context of applying both traditional econometric methods and several machine learning methods to the same dataset.


BRUNELLA BRUNO | Tenured Researcher, Finance Department and Baffi, Bocconi University

We investigate whether and how banks in the global syndicated loan market adjusted the pricing and supply of credit to account for higher climate transition risk. We provide a comprehensive measure of exposure to climate transition risk, considering three important risk drivers: the borrower’s carbon emissions, a policy shock represented by the 2015 Paris Agreement, and climate resilience and policy stringency of the country in which borrowers are located. 

The evidence is mixed and points to non-linear relations between lending variables and CO2 emissions. Policy events such as the Paris Agreement and government environmental awareness are significant climate risk drivers that, when combined, may amplify banks’ perception of climate transition risk.


AURÉLIA FÄH | Senior Sustainability Expert, Asset Management Association Switzerland (AMAS)

This article explores the pivotal role that the financial services sector plays in advancing sustainable finance, with a focus on the Swiss Stewardship Code published in October 2023 as a case study. It highlights the financial services sector’s inherent bias toward recognizing and capitalizing on the transformative opportunities presented by sustainable finance, emphasizing long-term value creation, risk management, and innovation. It contrasts market-based and regulatory approaches to sustainability, showing Switzerland’s preference for market- and principle-based approaches. 

The Swiss Stewardship Code, developed by the Asset Management Association of Switzerland and Swiss Sustainable Finance, is presented as a model for effective stewardship in sustainable investing. The article argues that this approach, emphasizing collaboration, innovation, and a proactive stance towards sustainability, not only combats greenwashing but also aligns financial flows with sustainability goals, underscoring the financial services sector’s critical role in driving sustainable economic, social, and environmental outcomes.


KARL SCHMEDDERS | Professor of Finance, IMD
MAXIMILIAN WERNER | Associate Director and Research Fellow, IMD

In this study, we analyze three decades of return data from listed private equity (LPE) companies, focusing on the return averages and volatilities of two notable market indices and comparing them to a global equity index. Our findings indicate that LPE has generated higher average returns, commensurate with its higher volatility, in comparison to the global index.

Additionally, we observe that, on average, LPE companies have traded at a discount to their book values since the Great Financial Crisis. Importantly, this discount exhibits a strong negative correlation with an indicator of macro-financial stress, which emerges as a predictive factor for LPE market performance.

MARK CHINEN | Professor, Seattle University School of Law

This article discusses efforts by policymakers to regulate AI through international human rights. It begins by surveying some of the human rights concerns that arise from AI applications. Because of the important role businesses are playing in the development of AI, the article then sketches the contours of international human rights law as it applies to firms.

Businesses have a responsibility to respect human rights, but until recently this has not been understood as a legal obligation. Recent legislation in Europe indicates that the norm is hardening, but there is resistance to this trend. Some of the reasons why are explored here. I join others, however, in arguing that as complex as some of these issues are, international human rights as a set of principles and where appropriate, as legal obligations, are the best overarching framework for governing transformative technologies such as AI.


The integration of artificial intelligence systems within the financial services industry has the potential to transform business operations, improve customer relations, and enhance regulatory compliance efforts. However, its adoption is not without risk; the integration of AI raises significant ethical concerns and threatens market integrity, data privacy, consumer protection, and other modern tenets of law. While these concerns are not necessarily new to the financial services industry, they do present barriers to the incorporation of AI technology. 

This article explores both the benefits and risks associated with AI in the context of financial services, discussing the relevant policy considerations and current regulatory landscape. It synthesizes current research and industry invites to provide an overview of the opportunities and challenges associated with the use of AI within financial services while addressing the lack of certainty currently observed in formulating an approach for broader incorporation. In doing so, this article offers valuable insights for financial professionals and researchers in navigating the rapidly evolving landscape of AI-driven financial services.

CHENG-YUN (CY) TSANG | Associate Professor and Executive Group Member (Industry Partnership), Centre for Commercial Law and Regulatory Studies (CLARS), Monash University Faculty of Law (Monash Law)1
PING-KUEI CHEN | Associate Professor, Department of Diplomacy, National Chengchi University

Central bank digital currencies (CBDCs) have gained momentum in the global financial system in recent years. Its impact on global financial regulations cannot be underestimated. Despite various motives for issuing CBDCs, the circulation of different CBDCs in the global financial networks will require central banks to revise the existing rules or formulate new ones.

In this process, geopolitics has a significant role. The global financial order may head to Balkanization or harmonization. This paper discusses the counteracting forces that draw regulatory changes in opposite directions. CBDCs may change the order on payment systems, settlement and clearing mechanisms, privacy protection, capital control measures, and AML/CFT measures. 

Geopolitical concerns on currency sovereignty and competition over fintech innovations can simultaneously encourage cooperation and confrontation. Central banks, financial intermediaries, and the private sector should be ready to cope with significant changes in the global financial order. 

We argue that technological developments and geofinancial concerns will remain the predominant areas of focus for years to come. They will determine the scope and intensity of geopolitical competition, and then spill over to global finance.

JOSEF SCHROTH | Research Advisor, Financial Stability Department, Bank of Canada

Following the 2007-09 global financial crisis, policymakers and standard setters made an important change in how they think about the regulation of banks. While they have always been focusing on the health of banks, they now explicitly do so to make sure that there are no sudden contractions in credit supply. 

Consequently, success of regulatory policy is now measured not only by market liquidity or whether there are losses to deposit insurance agencies, but also by whether the supply of credit is sufficiently stable. Higher capital (buffer) requirements, paired with regulatory stress tests, are key policy innovations to support stable credit supply. These policy innovations impose costs on banks today, but their intended future benefits are not well understood. 

This article discusses design features that determine whether the innovations’ intended benefits would materialize.

PATRICK CERNEA | Director, Data Strategy and Governance, York University, Canada
MARGARET KIERYLO | Assistant Vice-President, Institutional Planning and Chief Data Officer, York University, Canada

This article explores the critical role of data governance in the context of higher education. The authors highlight the strategic importance of establishing comprehensive data governance frameworks to enable data-informed decision making and argue that data governance can enhance strategic enrolment management, efficiency and effectiveness, and enable innovation. 

The authors present a detailed exploration of the strategies for building data governance capabilities within higher education institutions. They outline the process of setting data governance goals, selecting operating models for data governance, considering resourcing models, defining roles and responsibilities, establishing data governance committees, and identifying metrics to assess progress. 

Practical applications of data governance, including metadata management, data quality management, and ensuring regulatory compliance and ethical use of data, are discussed to illustrate how institutions can enhance their data environment. The authors conclude by exploring future trends and emerging issues in data governance within higher education, pointing to the lag in data governance advancement compared to other sectors and the imperative for post-secondary institutions to adopt robust data governance frameworks to remain competitive and innovative.


LAMIA IRFAN | Applied Research Lead, Innovation Design Labs, Capco

In the ever-evolving fraud prevention landscape, mental models are emerging as a game-changer. By serving as cognitive frameworks that guide our understanding and interpretation of fraudulent activities, mental models enable financial institutions to elevate their fraud prevention efforts. 

This article explores the role of mental models in preventing fraud, from pattern recognition to decision-making frameworks, highlighting their significance in safeguarding assets and enhancing efficacy.