Big Data and Artificial Intelligence in Digital Finance

This open access book presents how cutting-edge digital technologies like Big Data, Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector. The book illustrates how recent advances in these technologies facilitate banks, FinTech, and financial institutions to collect, process, analyze, and fully leverage the very large amounts of data that are nowadays produced and exchanged in the sector. To this end, the book also describes some more the most popular Big Data, AI and Blockchain applications in the sector, including novel applications in the areas of Know Your Customer (KYC), Personalized Wealth Management and Asset Management, Portfolio Risk Assessment, as well as variety of novel Usage-based Insurance applications based on Internet-of-Things data. Most of the presented applications have been developed, deployed and validated in real-life digital finance settings in the context of the European Commission funded INFINITECH project, which is a flagship innovation initiative for Big Data and AI in digital finance. This book is ideal for researchers and practitioners in Big Data, AI, banking and digital finance

Infrastructure finance in Europe: Composition, evolution and crisis impact

This article is the first attempt to compile comprehensive data on infrastructure finance in Europe. We decompose infrastructure finance by institutional sector (i.e. public versus private) into its main components, which consist of traditional public procurement, project finance and finance by the corporate sector, and analyse how the roles of the public and private sectors in financing infrastructure have evolved over time, especially during the recent economic and financial crisis. In contrast with government finance that is slightly up, private finance, in particular project finance through Publi-Private Partnerships, has fallen substantially during the recent crisis, reversing, at least temporarily, the longer-term trend of more private and less public financing of infrastructure.Infrastructure investment; Public-Private Partnerships; Project finance; Crisis impact

The economics of infrastructure finance: Public-Private Partnerships versus public provision

We examine the economics of infrastructure finance, focusing on public provision and Public-Private Partnerships (PPPs). We show that project finance is appropriate for PPP projects, because there are few economies of scope and because assets are project specific. Furthermore, we suggest that the higher cost of finance of PPPs is not an argument in favour of public provision, since it appears to reflect the combination of deficient contract design and the cost-cutting incentives embedded in PPPs. Thus, in the case of a correctly designed PPP contract, the higher cost of capital may be the price to pay for the efficiency advantages of PPPs. We also examine the role of government activities in PPP financing (e.g. revenue guarantees, renegotiations) and their consequences. Finally, we discuss how to include PPPs revenue guarantees and the results of PPP contract negotiation in the government balance sheet.Fiscal accounting; PPP premium; Project finance; Renegotiations; Revenue guarantees; Special Purpose Vehicule

Securing Our Economic Future

The American economy is in the midst of a wrenching crisis, one caused by the COVID-19 pandemic and aggravated further by a series of climate-driven natural disasters. While the economy has made some steps towards recovery, the pandemic has laid bare the reality that too many Americans are unable to meet many of their urgent and basic needs. At the same time, it has become painfully clear that American society is not equipped to deal with the risks emerging from our changing climate. This book is a contribution towards policy options for addressing these challenges. Although it was largely written before the pandemic crises beset our country, the analyses, diagnoses, and prescriptions contained within all shed new light on the underlying fragilities that have since been exposed. The volume is composed of nine commissioned chapters and is divided into three sections, covering the 'Economics of the American Middle Class'; the 'Geographic Disparities in Economic Opportunity'; and the 'Geopolitics of the Climate and Energy Challenge and the US Policy Response.' Part I focuses on the economic wellbeing of the American middle class and the chapters in this section evaluate the prevailing narrative of its decline. The chapters in part II investigate the large variation in income and economic opportunities across places, and include a specific policy proposal for emergency rental assistance. Part III is devoted to the global climate crisis. The chapters in this final section emphasize the mounting social and economic costs of inaction and discuss potential policy approaches for tackling the climate challenge

Analytical validation of innovative magneto-inertial outcomes: a controlled environment study.

peer reviewe

Waiting times, aging, chronic conditions and health care costs : teachings from the life-cycle model

Cette thèse étudie plusieurs défis auxquels sont confrontés les systèmes de santé modernes avec des modèles calibrés inspirés des théories du capital-santé et du cycle de vie. Dans le premier chapitre, nous développons le premier modèle dynamique de demande de soins de santé dans un cadre public. Dans ce modèle, les agents choisissent d'utiliser les soins si la désutilité encourue en file d'attente est dominée par les gains dynamiques permis par l'impact des soins sur la santé. Nous intégrons ensuite cette modélisation de la demande dans un modèle macroéconomique, que nous calibrons à l'aide de données québécoises de 2005. À l'aide de simulations, nous questionnons la pertinence, du point de vue du bien-être social, de permettre à de longs temps d'attente d'émerger afin de réduire les coûts de santé. Nous trouvons que les temps d'attente constituent un mécanisme faible de rationnement de la demande et mènent à d'importants coûts sociaux. En contrepartie, toutes les politiques simulées menant à des réductions de temps d'attente génèrent des gains substantiels de bien-être. Dans le second chapitre, nous étendons notre méthodologie afin d'étudier les impacts du vieillissement de la génération du "baby-boom" sur les systèmes publics de santé. Nous faisons évoluer la distribution d'agents selon les prévisions des démographes de l'Institut de la statistique du Québec (ISQ) et anticipons l'évolution de l'utilisation des soins et des temps d'attente de 2005 à 2050. Nous trouvons que la politique actuelle d'augmentation de 5% par an du budget de la santé mènera à un allongement important des temps d'attente d'ici 2030, et ce malgré une augmentation marquée de la part des coûts de santé dans l'économie. D'ici à 2050, nous estimons qu'il sera nécessaire de doubler la part de l'économie allouée au système de santé afin de maintenir les temps d'attente à leurs niveaux de 2005. Dans le dernier chapitre, nous nous questionnons sur l'évolution à venir de la santé, de la longévité et des coûts des soins des États-Unis d'Amérique (É-U). Nous développons un modèle de demande de soins dont le point focal est l'incertitude pour les agents de contracter une maladie chronique. Nous calibrons ce modèle sur l'évolution des données américaines de 1985 à 2005. Selon nos simulations, les dépenses de santé atteindront 22% du PIB des É-U d'ici 2050 si les tendances récentes continuent au même rythme. Nous trouvons que la prévalence de maladies chronique continuera de croître durant cette période, mais n'entraînera pas d'augmentations importantes de coûts des soins. Ce sont plutôt les progrès technologiques en santé et l'augmentation des revenus qui entraîneront la hausse des dépenses.\ud ______________________________________________________________________________ \ud MOTS-CLÉS DE L’AUTEUR : Systèmes publics de santé, demande de soins de santé, coûts des soins de santé, temps d'attente, vieillissement, maladies chroniques

Big Data and Artificial Intelligence in Digital Finance

This open access book presents how cutting-edge digital technologies like Big Data, Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector. The book illustrates how recent advances in these technologies facilitate banks, FinTech, and financial institutions to collect, process, analyze, and fully leverage the very large amounts of data that are nowadays produced and exchanged in the sector. To this end, the book also describes some more the most popular Big Data, AI and Blockchain applications in the sector, including novel applications in the areas of Know Your Customer (KYC), Personalized Wealth Management and Asset Management, Portfolio Risk Assessment, as well as variety of novel Usage-based Insurance applications based on Internet-of-Things data. Most of the presented applications have been developed, deployed and validated in real-life digital finance settings in the context of the European Commission funded INFINITECH project, which is a flagship innovation initiative for Big Data and AI in digital finance. This book is ideal for researchers and practitioners in Big Data, AI, banking and digital finance

Three Essays on Financial Economics

This dissertation presents three essays in financial economics. The essays discuss how market frictions can affect outcomes in the real economy, the returns earned by investors, and the investment decisions made by asset managers. The first essay studies how the liquidity of assets can affect outcomes in the real economy. In particular, it focuses on the life settlement market to show how increased liquidity of life insurance contracts are causally linked to greater life longevity. The second essay studies how inside investments relate to managerial compensation and fund performance. The essay focuses on the decreasing returns to scale to arbitrage strategies and the profit maximizing motive of asset managers as the central friction affecting return. The final essay analyzes the role that information acquisition and communication have on the choice to be a principal, agent, or both. The results emphasize how the choice to be either a principal or an agent strictly dominate the mixed strategy of being both, in a highly generalized model

Delft Delta Design:

In 2008, Hurricane Ike devastated Bolivar Peninsula, narrowly missing the more heavily industrialized and populated areas in the region. In the aftermath of the hurricane, the Severe Storm Prediction, Education and Evacuation from Disasters (SSPEED) Center at Rice University in Houston, and Texas A&M University in Galveston (TAMUG) led initiatives to propose and design flood mitigation strategies. In collaboration with TAMUG and the SSPEED Center, students and researchers at Delft University of Technology in the Netherlands have been investigating regional strategies for flood risk reduction. In this publication they and their Texas counterparts reflect on the research, design, and insight that has sprouted from this collective endeavour.   &nbsp