Monitoring bank performance in the presence of risk

This paper proposes a managerial control tool that integrates risk in efficiency measures. Building on existing efficiency specifications, our proposal reflects the real banking technology and accurately models the relationship between desirable and undesirable outputs. Specifically, the undesirable output is defined as nonperforming loans to capture credit risk, and is linked only to the relevant dimension of the output set. We empirically illustrate how our efficiency measure functions for managerial control purposes. The application considers a unique dataset of Costa Rican banks during 1998–2012. Results’ implications are mostly discussed at bank-level, and their interpretations are enhanced by using accounting ratios. We also show the usefulness of our tool for corporate governance by examining performance changes around executive turnover. Our findings confirm that appointing CEOs from outside the bank is associated with significantly higher performance ex post executive turnover, thus suggesting the potential benefits of new organisational practices.Peer ReviewedPostprint (author’s final draft

Issues and Challenges in Applications of Artificial Intelligence to Nuclear Medicine -- The Bethesda Report (AI Summit 2022)

The SNMMI Artificial Intelligence (SNMMI-AI) Summit, organized by the SNMMI AI Task Force, took place in Bethesda, MD on March 21-22, 2022. It brought together various community members and stakeholders from academia, healthcare, industry, patient representatives, and government (NIH, FDA), and considered various key themes to envision and facilitate a bright future for routine, trustworthy use of AI in nuclear medicine. In what follows, essential issues, challenges, controversies and findings emphasized in the meeting are summarized

Review and synthesis of problems and directions for large scale geographic information system development

Problems and directions for large scale geographic information system development were reviewed and the general problems associated with automated geographic information systems and spatial data handling were addressed

Towards AI Standards Whitepaper: Thought-leadership in AI legal, ethical and safety specifications through experimentation

With the rapid adoption of algorithms in business and society there is a growing concern to safeguard the public interest. Researchers, policy-makers and industry sharing this view convened to collectively identify future areas of focus in order to advance AI standards - in particular the acute need to ensure standard suggestions are practical and empirically informed. This discussion occurred in the context of the creation of a lab at UCL with these concerns in mind (currently dubbed as UCL The Algorithms Standards and Technology Lab). Via a series of panels, with the main stakeholders, three themes emerged, namely (i) Building public trust, (ii) Accountability and Operationalisation, and (iii) Experimentation. In order to forward the themes, lab activities will fall under three streams - experimentation, community building and communication. The Lab’s mission is to provide thought-leadership in AI standards through experimentation

Digital strategy implementation in process manufacturing firms: the Sirmax case.

The elaboration aims to investigate how to effectively implement a digital strategy in process manufacturing firms. After having analyzed literature and benchmark cases, the focus is on the digital strategy implementation proposal for Sirmax, a process manufacturing firm.ope

Proceed with Caution : Artificial Intelligence in Weapon Systems

Publisher PD

RTD Evaluation Toolbox. Assessing the Socio-Economic Impact of RTD-Policies

Abstract not availableJRC.J-Institute for Prospective Technological Studies (Seville