Regulatory Risk Research Articles

Automation of Data Validation Processes in Banking: A Case Study on Validating Albanian Identity Numbers

Abstract In the banking industry, data accuracy and integrity are paramount for ensuring regulatory compliance, operational efficiency, and risk management. However, manual data validation processes often lead to delays, errors, and inefficiencies, posing challenges for financial institutions. To address these issues, many banks are turning to automation to streamline data validation processes and improve accuracy. Using data automation, banks optimize time-consuming manual tasks such as data entry, validation, and retrieval by creating automated software processes that execute these tasks quickly and accurately. This case study examines how a hypothetical bank uses automation to improve data validation processes, focusing on Albanian Identity Numbers (AINs). By automating validation tasks, the bank enhances accuracy, compliance, and efficiency, mitigating the limitations of manual processes. The study outlines the implementation steps, discusses results, and highlights the importance of automating data validation in the banking sector.

Reduced time to efficacy signals in advanced cancer trials using Chauhan weighted trajectory analysis.

e23028 Background: As Kaplan-Meier (KM) analyzes single unidirectional endpoints, most advanced cancer randomized clinical trials (RCTs) are powered for a 10 endpoint of either progression free survival (PFS) or overall survival (OS). This disregards efficacy information carried by stable disease (SD), partial response (PR), and complete response (CR) that may precede progressive disease (PD) and death. Chauhan Weighted Trajectory Analysis (CWTA), a generalization of KM, permits simultaneous evaluation of multiple rank ordered endpoints. We hypothesized that using CWTA with all efficacy inputs could expedite RCT efficacy signals. Methods: We performed 100-fold simulations of RCTs in advanced cancer and determined the time to first significant efficacy signal (p < 0.05) for KM PFS and OS (logrank test) and CWTA (weighted logrank test). RCTs were stochastically generated at defined sample size (SS) allocated 1:1 to control or intervention and run for 60 months. Rank ordered health statuses were CR = 0, PR = 1, SD = 2, PD = 3, and Death = 4. All patients we assigned SD at time 0 and, each month, were capable of response (PR then CR), maintained SD, or irreversible exacerbation to PD or Death. Event probabilities were modified between groups as defined by a hazard ratio (HR). We modeled a control group CR rate of ~10% and a PR rate of ~50% to reflect first-line advanced cancer RCTs with a dropout rate of 10% over 60 months. At increments of SS and HR, we determined the mean and standard deviation of time-to-efficacy signals. Results: CWTA markedly reduced the time-to-efficacy signals when compared to KM PFS (23% to 67%) and KM OS (43% to 82%) (Table 1). Conclusions: CWTA, by incorporating the entirety of the cancer trajectory including disease response, progression, and death, meaningfully expedites the efficacy signals of cancer treatments compared to KM PFS and OS. We have previously reported CWTA increases trial power and reduces sample size requirements (Chauhan U, Zhao K, Walker J, Mackey JR; 2023. DOI: 10.3390/biomedinformatics3040052). Using CWTA rather than KM reduces trial duration, cost, and numbers of patients needed to evaluate therapies in advanced cancer, while reducing the regulatory risk inherent in powering a trial for a single KM primary endpoint. [Table: see text]

Bitcoin: The Fintech Revolution from Its Origins to the Future

This study delves into Bitcoin's origins, development, and impact on the future of Fintech, answering key questions about how the cryptocurrency will revolutionize the Fintech landscape. The study is significant because it provides insight into the challenges and opportunities posed by decentralized finance, which is increasingly relevant in the academic fields of finance and technology. The study uses a multidisciplinary approach to understand Bitcoin's technical underpinning, global acceptance, and regulatory environment through a comprehensive analysis of Bitcoin white papers, historical data, and regulatory documents. The research methodology includes a detailed examination of blockchain technology, the workings of the Bitcoin network, and the factors that influence Bitcoin price trends. The findings reveal Bitcoin as a decentralized monetary system that introduces a new paradigm in financial transactions, offering transparency, security, and potentially high returns. However, it also presents significant regulatory challenges, market volatility and risks that need to be managed. The study identified key factors that affect the price of bitcoin, such as supply and demand dynamics, market sentiment, macroeconomic conditions, and technological advances. The implications of this work are far-reaching as it highlights the need for a balanced approach to cryptocurrency regulation that promotes innovation while mitigating risk. The study contributes to the academic discussion by providing a nuanced understanding of Bitcoin's role in the evolving financial ecosystem and its potential impact on monetary policy, financial stability, and global economic dynamics.

Navigating travel decisions in health crises: The interplay of message framing, regulatory focus, and perceived risk

This study investigates the impact of promotional message framing on domestic tourists' travel intentions during a health crisis, exploring the moderating effects of regulatory focus and perceived risk. Utilizing a 2 × 2 × 2 between-subject factorial design, two experiments were conducted with data collected from domestic tourists. The findings reveal that promotion-focused tourists prefer emotionally resonant gain-framed messages with lower discounts and show lower susceptibility to health risks compared to their prevention-focused counterparts. The interaction of gain-framed messages with low discount depth resulted in increased travel intentions despite the health crisis. On the other hand, prevention-focused tourists exhibited no significant change in travel intentions in response to differently framed messages. This study extends the promotional framing literature by incorporating regulatory focus and risk perception, offering practical implications for the tourism industry, particularly during a time of health crisis.

Fintech industry risk: does investor attention matter?

ABSTRACT The Fintech industry risk challenges the stability of China’s financial system. This paper makes the first attempt to capture the dynamics of the Fintech industry risk, represented by Fintech stock volatility, from the investor attention perspective. The novelty of this paper is that we fully consider the regime changes in the Fintech industry risk by adopting the AR-MS-GARCH-MIDAS with the Markov regime-switching process incorporated in the short-run volatility component, long-run volatility component, or both. We find that (1) Fintech industry risk is subject to structural breaks, (2) higher investor attention tends to alleviate the Fintech stock volatility, while the negative impact strengthens when the industry is in volatile condition, (3) investor attention contributes to improving the accuracy of the Fintech stock volatility forecasting, (4) considering the structural breaks of investor attention is important in volatility forecasting. We enrich the literature on the Fintech industry risk regulation, stock volatility forecasting, and the attention allocation theory.

The Evergrande Effect: Unraveling the Housing Crisis in China and its Global Ramifications

The Chinese real estate market, epitomized by the tumultuous trajectory of Evergrande Group, stands at the forefront of global economic discourse. This abstract encapsulates the intricate interplay of factors shaping this market, from speculative dynamics and urbanization trends to regulatory interventions and systemic risks. It examines the fallout of Evergrande's collapse, illuminating its ripple effects on China's economy and the reverberations felt across international financial markets. As policymakers grapple with the aftermath and chart a course forward, this abstract offers insights into the challenges and opportunities inherent in navigating the complex terrain of the Chinese real estate landscape.

Sustainable nanomaterials' role in green supply chains and environmental sustainability

The review explores the pivotal role of sustainable nanomaterials in promoting green supply chains and advancing environmental sustainability. Nanotechnology has emerged as a promising field for developing innovative materials with enhanced properties and reduced environmental impacts. Sustainable nanomaterials, characterized by their eco-friendly synthesis methods, biodegradability, and low toxicity, offer transformative opportunities for enhancing the sustainability of supply chains across diverse industries. This review examines the potential applications of sustainable nanomaterials in green supply chains, encompassing areas such as renewable energy, water purification, waste management, and sustainable packaging. By leveraging the unique properties of nanomaterials, such as high surface area-to-volume ratio, catalytic activity, and tunable properties, businesses can develop sustainable solutions to address pressing environmental challenges. Case studies and examples highlight successful integration of sustainable nanomaterials into supply chain practices, showcasing their ability to reduce resource consumption, minimize waste generation, and mitigate environmental impacts. The review also discusses challenges and considerations associated with the adoption of sustainable nanomaterials, including regulatory compliance, risk assessment, and ethical considerations. Strategies for promoting responsible nanotechnology practices and fostering collaboration among stakeholders are proposed, emphasizing the importance of interdisciplinary approaches and stakeholder engagement in achieving sustainable supply chain goals. In conclusion, the integration of sustainable nanomaterials into green supply chains holds immense potential for driving environmental sustainability, innovation, and long-term prosperity. Keywords: Sustainable Nanomaterials, Green Supply Chains, Environmental Sustainability, Circular Economy, Nanotechnology, Supply Chain Optimization

A Novel Approach to Integrate Human Biomonitoring Data with Model Predicted Dietary Exposures: A Crop Protection Chemical Case Study Using Lambda-Cyhalothrin.

The appropriate use of human biomonitoring data to model population chemical exposures is challenging, especially for rapidly metabolized chemicals, such as agricultural chemicals. The objective of this study is to demonstrate a novel approach integrating model predicted dietary exposures and biomonitoring data to potentially inform regulatory risk assessments. We use lambda-cyhalothrin as a case study, and for the same representative U.S. population in the National Health and Nutrition Examination Survey (NHANES), an integrated exposure and pharmacokinetic model predicted exposures are calibrated to measurements of the urinary metabolite 3-phenoxybenzoic acid (3PBA), using an approximate Bayesian computing (ABC) methodology. We demonstrate that the correlation between modeled urinary 3PBA and the NHANES 3PBA measurements more than doubled as ABC thresholding narrowed the acceptable tolerance range for predicted versus observed urinary measurements. The median predicted urinary concentrations were closer to the median measured value using ABC than using current regulatory Monte Carlo methods.

Theoretical insights into IT governance and compliance in banking: Perspectives from African and U.S. regulatory environments

This review paper provides a comprehensive comparative analysis of IT governance and compliance within the banking sectors of Africa and the U.S., highlighting the intricacies of navigating diverse regulatory environments. Through examining governance strategies, compliance mechanisms, and best practices, the paper underscores the adaptation of frameworks like COBIT, ISO/IEC 27001, and ITIL to meet regional regulatory demands and operational challenges. Key insights reveal significant differences in regulatory landscapes, technological maturity, and cybersecurity and risk management approaches. The analysis identifies best practices and lessons that can be leveraged globally, suggesting areas for future research including emerging technologies and the impact of global regulations. This work aims to enhance understanding of IT governance and compliance, offering valuable perspectives for banks, regulators, and policymakers. Keywords: IT Governance, Compliance, Banking Sector, Regulatory Environment, Cybersecurity, Emerging Technologies.

Overvoltage risk regulation strategy with distributed energy application in a distribution network based on the Stackelberg game

Along with the increasing low-carbon demand of the power system, the access of a high percentage of renewable energy resources to the distribution network has a large impact on the voltage fluctuation of the system and reduces the operational reliability. In this paper, we consider utilizing the reactive capacity of distributed resources to participate in system voltage regulation to reduce node loss of load probability (LOLP) caused by node overvoltage faults and propose an overvoltage risk regulation strategy for the interaction between distribution network operators (DSOs) and distributed users in the framework of the Stackelberg game. First, the nodes are clustered and analyzed based on the two-dimensional indexes of node voltage regulation ability, and different voltage regulation compensation tariffs are assigned. Second, the cost-benefit model of voltage regulation for the leader and follower sides and the node LOLP model are constructed to measure the reliability of the system. The Stackelberg game is used to co-optimize the two parties’ compensation tariffs and voltage regulation strategies. The optimal solution of voltage regulation under the equilibrium of the game is obtained by solving using the particle swarm optimization (PSO) algorithm. Based on the IEEE-33 node system, a case study is carried out to verify that the proposed overvoltage risk regulation strategy can maximize the benefits of the regulator participants while enhancing the operational reliability of the system.

A qualitative analysis of cascading effects of critical infrastructure service failure post torrential floods in formal & informal settlement: the study-case of Medellin city, Colombia

ABSTRACT Critical infrastructure (CI) services are crucial to the functioning of modern communities, and a single CI failure can cause cascading effects through a network of services, impacting an entire city. Challenges such as climate change and rapid urbanisation are increasing the risk of cascading effects of CI failure, particularly impacting the urban poor in peri-urban and informal settlements. This study uses a systems thinking approach to validate the hypothesis if CI services are susceptible to generating severe cascading effects in informal than formal settlements. Qualitative data was collected on cascading effects via interviews and focus group discussion in a formal and an informal settlement in Medellin, Colombia. The responses were analysed and structured using a service chain framework and a Causal Loop Diagram. Our findings show that cascading effects vary between the formal and informal contexts concerning CI service availability and accessibility and may be attributed to differences in demography, geography, socio-economic development, risk regulations, community coping capacities and other factors associated with urban development.

Possible harms of artificial intelligence and the EU AI act: fundamental rights and risk

Various actors employ the notion of risk when they discuss the future role of Artificial Intelligence (AI) in society – sometimes as a general pointer to possible unwanted consequences of the underlying technologies, sometimes oriented towards a political regulation of AI risks. Mostly discussed within a legal or ethical framework, we still lack a perspective on AI risks based on sociological risk research. Building on systems-theoretical thinking about risk and society, this article analyses the potential and limits of a risk-based regulation of AI, in particular with regard to the notion of harm to fundamental rights. Drawing on the AI Act, its earlier drafts and related documents, the paper analyses how this regulatory framework delineates harms of AI and which implications the chosen delineation has for the regulation. The results show that fundamental rights are invoked as legal rules, as values and as a foundation for trustworthiness of AI in parallel to being identified as at risk from AI. The attempt to frame all possible harms in terms of fundamental rights creates communicative paradoxes. It opens the door to a political classification of high-risk AI systems as well as a future standard-setting that is removed from systematic concerns about fundamental rights and values. The additional notion of systemic risk, addressing possible risks from general-purpose AI models, further reveals the problems with delineating harms of AI. In sum, the AI Act is unlikely to achieve what it aims to do, namely the creation of conditions for trustworthy AI.

Refinement of flavour substance intake estimates using probability of addition: A proposed method based on sales data

AbstractMost dietary intake estimates used in the regulatory risk assessment of flavouring substances assume that the flavouring substance is present in all foods at a given concentration. They do not account for the use of alternate flavouring substances for the same taste modality, nor do they consider the use of differing concentrations within a particular food category. This highly conservative assumption leads to an over‐estimation of exposure. To refine this assumption in exposure models, the probability of addition can be utilised. In this study, a methodology to estimate the probability of addition was developed, using the volume of a flavouring substance sold for flavours created for a particular food category against its total volume sold for all flavouring use. The method was trialled, as a proof of principle, using historical data sets of two test flavouring substances, benzaldehyde (a large volume/use material) and bornyl acetate (a low volume/use material), and the impact on dietary exposure assessment was assessed. The resulting exposure estimates for both flavouring substances were shown to be significantly lower than those without the incorporation of probability of addition, demonstrating that current methods are overly conservative and that the use of probability of addition provides a more realistic estimate of exposure of flavouring substances present in foods.

The role of AI capabilities in environmental management: Evidence from USA firms

This study investigates the role of Artificial Intelligence (AI) capabilities in influencing firms' greenwashing behaviors. We find a robust negative association between firms' AI capabilities and unrepresentative environmental disclosure. An instrumental variable approach is employed to establish causality. The effects are more pronounced for firms (1) with a greater exposure to regulatory climate risk, (2) managed by Republican-leaning managers, (3) with stronger governance structures, (4) possessing greater product market pricing power, (5) operating in multiple regions, and (6) with CEOs with higher pay-for-performance sensitivity. We further demonstrate that AI capabilities aid firms in transitioning to green operations through engaging in green and clean innovation. Finally, we find that AI capabilities correlate with lower greenhouse gas emissions. Overall, our findings shed light on the real impact of AI-related technologies in the energy industry.

The use of effect biomarkers in chemical mixtures risk assessment – Are they still important?

Human epidemiological studies with biomarkers of effect play an invaluable role in identifying health effects with chemical exposures and in disease prevention. Effect biomarkers that measure genetic damage are potent tools to address the carcinogenic and/or mutagenic potential of chemical exposures, increasing confidence in regulatory risk assessment decision-making processes. The micronucleus (MN) test is recognized as one of the most successful and reliable assays to assess genotoxic events, which are associated with exposures that may cause cancer. To move towards the next generation risk assessment is crucial to establish bridges between standard approaches, new approach methodologies (NAMs) and tools for increase the mechanistically-based biological plausibility in human studies, such as the adverse outcome pathways (AOPs) framework. This paper aims to highlight the still active role of MN as biomarker of effect in the evolution and applicability of new methods and approaches in human risk assessment, with the positive consequence, that the new methods provide a deeper knowledge of the mechanistically-based biology of these endpoints.

Recruiting and cultivating future leaders in laboratory science.

Technological in-vitro fertilization (IVF) advancements originate in the embryology laboratory, and are accompanied by increased regulatory oversight and risk management. Stakes have never been higher or the need greater for the recruitment and cultivation of leaders in laboratory science to navigate the direction of IVF. Current thought leaders in state-of-the-art laboratories must prioritize this mission to optimize and preserve the future of IVF. Leaders in laboratory science must be able to speak to patients, the lay public, business leaders, scientific colleagues and clinical embryologists. While technically gifted, laboratory leaders may benefit from leadership training. Recruitment of scientists into IVF is currently challenging due to a lack of branding and no clear pipeline for new scientists to enter the field. Once recruited however, cultivation of new leaders requires coaching and skill acquisition over time, in order to create multifaceted laboratory leadership. Laboratory leaders are typically recruited based on education and experience to lead teams of embryologists. These leaders will adopt new technologies in the laboratory. Therefore, laboratory leaders play a powerful role in IVF requiring leadership skills ultimately driving patient outcomes. These laboratory directors must possess innate leadership abilities or learn how to lead their teams.

The health risks of generative AI-based wellness apps.

Artificial intelligence (AI)-enabled chatbots are increasingly being used to help people manage their mental health. Chatbots for mental health and particularly 'wellness' applications currently exist in a regulatory 'gray area'. Indeed, most generative AI-powered wellness apps will not be reviewed by health regulators. However, recent findings suggest that users of these apps sometimes use them to share mental health problems and even to seek support during crises, and that the apps sometimes respond in a manner that increases the risk of harm to the user, a challenge that the current US regulatory structure is not well equipped to address. In this Perspective, we discuss the regulatory landscape and potential health risks of AI-enabled wellness apps. Although we focus on the United States, there are similar challenges for regulators across the globe. We discuss the problems that arise when AI-based wellness apps cross into medical territory and the implications for app developers and regulatory bodies, and we outline outstanding priorities for the field.

Research on Tax Risk Regulation and Strategic Management in the Context of Big Data

With the rapid development of big data, big data has been more and more applied in all walks of life. Under the big data environment, massive big data provides convenience for regional tax risk control and strategic decision-making but also increases the difficulty of data supervision and management. By analyzing the status quo of big data and tax risk management, this paper finds many problems and puts forward effective countermeasures for tax risk supervision and strategic management by using big data.

New approach methods to assess developmental and adult neurotoxicity for regulatory use: a PARC work package 5 project.

In the European regulatory context, rodent in vivo studies are the predominant source of neurotoxicity information. Although they form a cornerstone of neurotoxicological assessments, they are costly and the topic of ethical debate. While the public expects chemicals and products to be safe for the developing and mature nervous systems, considerable numbers of chemicals in commerce have not, or only to a limited extent, been assessed for their potential to cause neurotoxicity. As such, there is a societal push toward the replacement of animal models with in vitro or alternative methods. New approach methods (NAMs) can contribute to the regulatory knowledge base, increase chemical safety, and modernize chemical hazard and risk assessment. Provided they reach an acceptable level of regulatory relevance and reliability, NAMs may be considered as replacements for specific in vivo studies. The European Partnership for the Assessment of Risks from Chemicals (PARC) addresses challenges to the development and implementation of NAMs in chemical risk assessment. In collaboration with regulatory agencies, Project 5.2.1e (Neurotoxicity) aims to develop and evaluate NAMs for developmental neurotoxicity (DNT) and adult neurotoxicity (ANT) and to understand the applicability domain of specific NAMs for the detection of endocrine disruption and epigenetic perturbation. To speed up assay time and reduce costs, we identify early indicators of later-onset effects. Ultimately, we will assemble second-generation developmental neurotoxicity and first-generation adult neurotoxicity test batteries, both of which aim to provide regulatory hazard and risk assessors and industry stakeholders with robust, speedy, lower-cost, and informative next-generation hazard and risk assessment tools.

Exploring Financial Risks and Risk Mitigation Strategies in Digital Currencies

This paper comprehensively analyzes the financial risks faced by digital currency, using digital renminbi as a case study. The risks include operational risks, privacy risks, legal and regulatory risks, currency sovereignty risks, and the impact on traditional financial systems. Corresponding risk mitigation strategies are proposed. By strengthening system architecture, employing advanced encryption technologies, enhancing legal and regulatory frameworks, maintaining policy stability, and promoting financial integration, these measures effectively mitigate financial risks associated with digital currency, fostering its sustainable development and innovation.