Search results

This chapter introduces what a digital ID is, why it is important, how it works, the design choices, as well as how central banks can collaborate with other stakeholders in promoting digital ID infrastructures for use in digital financial services.

Companies are increasingly benefiting from artificial intelligence (AI) applications in various domains, but also facing its negative impacts. The challenge lies in the lack of clear governance mechanisms for AI. While documentation is a key governance tool, standard software engineering practices are inadequate for AI. Practitioners are unsure about how to document AI, raising questions about the effectiveness of current documentation guidelines. This review examines whether AI documentation guidelines meet regulatory and industry needs for AI applications and suggests directions for future research.

A structured literature review was conducted. In total, 38 papers from top journals and conferences in the fields of medicine and information systems as well as journals focused on fair, accountable and transparent AI were reviewed.

This literature review contributes to the literature by investigating the extent to which current documentation guidelines can meet the documentation requirements for AI applications from regulatory bodies and industry practitioners and by presenting avenues for future research. This paper finds contemporary documentation guidelines inadequate in meeting regulators’ and professionals’' expectations. This paper concludes with three recommended avenues for future research.

This paper benefits from the insights from comprehensive and up-to-date sources on the documentation of AI applications.

The widespread application of smart technologies in services not only brings efficiency and convenience to consumers but also inevitably comes with negative effects. Therefore, this article aims to illustrate the impact of privacy invasion on consumers' intention to use smart services. Using distrust as a mediating variable, compare two different modes of interaction between voice and text, and study the positive impact of privacy commitment. This study aims to provide recommendations for smart service providers to make the consumer experience better.

This paper adopts an experimental approach, with data collection and hypothesis analysis by designing four different experiments.

The results show that the negative impact of privacy invasion on consumers' intention to use smart services is moderated by privacy commitments and interaction modes. This article verifies the mediating effect of distrust on consumers' intention to use when privacy invasion occurs and verifies the moderating effect of the interaction modes by comparing voice interaction with text interaction and demonstrates that text interaction mode will attenuate the mediating role of distrust in the path in privacy invasion. Besides, it also indicates that privacy commitments can moderate the relationship between privacy invasion’s effect on distrust and intention to use.

Focusing on privacy invasion, this study explores consumers' intention to use smart services, compares the two interaction modes of voice and text to explore their moderating effects, deeply explores consumer psychology and studies the mediating role of distrust and the moderating role of privacy commitment.

The purpose of this paper is to highlight the key technical challenges that derive from the recently proposed European Artificial Intelligence Act and specifically, to investigate the applicability of the requirements that the AI Act mandates to high-risk AI systems from the perspective of AI security.

This paper presents the main points of the proposed AI Act, with emphasis on the compliance requirements of high-risk systems. It matches known AI security threats with the relevant technical requirements, it demonstrates the impact that these security threats can have to the AI Act technical requirements and evaluates the applicability of these requirements based on the effectiveness of the existing security protection measures. Finally, the paper highlights the necessity for an integrated framework for AI system evaluation.

The findings of the EU AI Act technical assessment highlight the gap between the proposed requirements and the available AI security countermeasures as well as the necessity for an AI security evaluation framework.

AI Act, high-risk AI systems, security threats, security countermeasures.

The purpose of this study is to delve into the intricate terrain of assimilating sustainability practices into digital accounting and finance, centring on the transformative dynamics introduced by artificial intelligence (AI)-enabled FinTech. The primary objective is to scrutinize critical lacunae in existing literature, exploring how organizations can meticulously construct comprehensive sustainability frameworks. Simultaneously, the study investigates the protracted repercussions of AI-enabled FinTech on the enduring sustainability paradigms.

Executing a systematic literature review, the research engaged in the meticulous identification and assessment of a voluminous pool of 1,158 articles. Using a judicious two-phase strategy, the scrutiny distilled a mere 64 pertinent articles, subjecting them to rigorous evaluation encompassing methodologies, contributions and overall quality. The Fuzzy Delphi method was used to elicit expert opinions and facilitate consensus-building, leveraging fuzzy logic to accommodate uncertainties in the data.

The review navigates the convoluted impact of AI across diverse sectors, accentuating its transformative imprint on realms such as health care, finance and transportation. Specifically, in the financial domain, the discerning eye of AI-enabled FinTech optimizes investment portfolios, augments risk assessment, propels financial inclusion and streamlines the intricate landscape of sustainability reporting. The study meticulously pinpoints research gaps encompassing investment optimization, risk management, financial inclusion, sustainability reporting and ethical considerations within the intricate milieu of AI-enabled FinTech. This research contributes to the existing body of knowledge by synthesizing intricate thematic strands, discerning overarching trends and spotlighting critical voids in the synthesis of sustainability practices and AI-enabled FinTech. The findings resonate with far-reaching implications, emphasizing the exigency of comprehensive investigations into the longitudinal sustainability ramifications instigated by AI-enabled FinTech.

The study underscores the imperative of crafting robust ethical frameworks for the equitable and transparent deployment of AI solutions within the intricate landscape of FinTech. Moreover, this research stands poised to shape organizational strategies, inform regulatory frameworks and guide investment decisions, thereby catalyzing the cultivation of conscientious and sustainable financial practices.

Bank–fintech associations are significant globally, establishing purposeful eco-systems towards extending and complementing capabilities, reach and customer experiences. This paper aims to explore 39 leading fintechs in India catering across payments, lending, wealth management, regulation, neo-banks and other banking functions. Alongside fintechs, the research studies 19 leading banks (public and private) to understand the nature of bank–fintech associations in the Indian context.

The research focuses on narratives from leading banks and top fintechs in India, captured from public disclosures and leadership interviews. The study leverages qualitative research techniques, including grounded theory approaches of inductive analysis, to codify interview and narrative observations to discover relevant objectives, scenarios, challenges and outcomes in India-centric bank–fintech associations.

Bank–fintech associations in India are increasingly focusing on financial services portfolio diversification and improvement in customer experience. Simultaneously, both banks and fintechs, differentiate with innovations and extend offerings to target underserved customer segments. The associations are beneficial for both banks and fintechs in transforming offerings and improving efficiency, scale across channels. Through codification of observations, review of existing literature and evaluation of best practices, alongside subject matter expertise, the study evolves a generalized “Association Model”. The model can steer meaningful bank–fintech associations in India and globally. The association model relates to observables like objectives, enablers of bank–fintech associations, challenges and association-driven value outcomes. Built from study of practices, the proposed model is relevant for strategic orientation in bank–fintech associations.

The findings reveal practices in bank–fintech associations in India with significant learning opportunity for organizational leaders globally. Understanding the nature of association is relevant for strategic interventions, particularly in scenarios of inter-organization collaborations. Central banks, policymakers, governments, investors, banks and fintechs can use the derived association model to establish, govern and steer purposeful value-driven associations.

Although digital transformation (DT) has emerged as an important phenomenon for both research and practices, the influences remain inconclusive and inadequate. The emerging artificial intelligence (AI) technologies further complicate the understanding and practices of DT while understudied yet. To address these concerns, this study takes a process perspective to empirically investigate when and how digital-intelligence transformation can improve firm performance, aiming to enrich the literature on digital-intelligence transformation and strategic information systems (IS) field.

Drawing on the dynamic capability view and business agility, we took a process perspective to conceptualize and empirically examine the influence of digital-intelligence transformation and the process characteristics. Taking a continuous panel dataset of listed Chinese firms covering 2007 to 2020, we investigated digital-intelligence transformation’s effect on firm performance and the moderating roles of three strategic aspects: pace, scope and rhythm.

This study found that digital-intelligence transformation positively affects firm performance and is moderated by the characteristics of transformation processes (i.e. pace, scope and rhythm). Specifically, the high-paced and rhythmic transformation processes facilitate the positive relationship, while the large scope undermines the benefits of transformation. These relationships hold across various endogeneity and heterogeneity analyses.

Our findings provide valuable implications for digital-intelligence transformation and strategic IS field. First, this study enriches existing literature on digital-intelligence transformation by empirically investigating the influence from a process perspective. Moreover, this study provides insights into a comprehensive understanding of the complexity of digital-intelligence transformation and the influences of AI. Finally, this study provides practical implications on how to make digital-intelligence transformation to benefit firm performance.

The purpose of this paper is to examine the factors that influence Saudi Arabian users’ intentions to continue using fintech payment applications and their satisfaction with these applications.

The unified theory of acceptance and use of technology 2 and DeLone and McLean’s IS success model were integrated to provide a comprehensive framework. A questionnaire was distributed to 401 users of fintech payment applications, and the data collected was analysed using structural equation modelling to test the hypotheses.

The results reveal that factors such as social influence, price value and habit have a positive influence on the continued desire to use fintech payment applications, that the performance expectancy is positively influenced by the level of effort expectancy. Additionally, the quality of the system, service and information provided by the applications has a direct association with user satisfaction, as indicated by the IS Success Model. Moreover, it was observed that customer satisfaction with fintech payment applications positively affects their intention to continue using them.

This study addresses an important gap in the existing literature by examining the factors influencing Saudi Arabian consumers’ intentions to sustain the usage of fintech payment applications. Despite governmental support for the industry, understanding consumer behaviour and satisfaction with these applications remains limited, making this research timely and valuable.

The paper aims to examine the impacts and ethics of utilizing Artificial Intelligence (AI) in Indian policing. It explores both the positive and negative consequences of using AI, as well as the ethical considerations that have be taken into account.

This study is based on secondary sources of information, such as national and international reports, journal articles, and institutional websites that discuss the use of AI technology by the police in India.

AI has proven to be effective in policing, from preventing crime to identifying criminals, by detecting potential crimes in advance with fewer resources and in more areas. In India, the police use AI technology not only for facial recognition but also for crime mapping, analysis, and building blocks. However, factors such as caste, religion, language, and gender continue to cause conflict. India has shown a strong interest in using AI technology for policing, and wishes to accelerate its implementation in various policing contexts, including law and order. This paper calls for an assessment of the complexities and uncertainties brought about by new technologies in policing with ethical considerations.

This paper can provide valuable insights for policy-makers, academics, and practitioners engaged in discussions and debates concerning the ethical considerations associated with the adoption of AI tools in policing practices.