FinTech and AI in Finance (FinTAF)

Artificial Intelligence as a Strategic Decision Support Tool: Toward Optimizing Financial Decision-Making Models under Uncertainty

2026-01-19T10:42:20+00:00

Artificial intelligence (AI) is reshaping financial decision-making processes by enhancing analytical precision, reducing uncertainty, and enabling data-driven strategies. This research proposes an AI-driven strategic decision-support framework to optimize financial decision models in complex, uncertain environments. The framework integrates predictive analytics and optimization algorithms to help financial managers and policymakers improve investment decisions, risk assessment, and resource allocation.

Building on decision-engineering principles, the study conceptualizes a hybrid model combining elements of machine learning, data analytics, and cognitive decision theory to strengthen the robustness and adaptability of strategic financial decisions. The proposed approach is structured to accommodate dynamic financial and market data, allowing for continuous improvement of forecasts and decision outcomes as new information becomes available.

Preliminary results suggest that AI-enhanced decision frameworks can improve forecasting reliability and strategic responsiveness, particularly in contexts characterized by volatility and incomplete information. This research contributes to the growing body of work at the intersection of artificial intelligence and financial management, offering both theoretical and practical insights for the design of intelligent financial systems. This conceptual study also lays the groundwork for a forthcoming empirical validation using financial datasets to evaluate the framework’s robustness and adaptability.

FinTech, Artificial Intelligence, and Financial Inclusion: Transforming Global Finance through Innovation, Regulation, and Ethics

2026-02-02T10:07:07+00:00

The convergence of Financial Technology (FinTech) and Artificial Intelligence (AI) is redefining the global financial ecosystem, transforming access, efficiency, and inclusion across both developed and emerging economies. This study examines the regulatory, ethical, and policy dimensions of AI-driven FinTech, highlighting its dual impact as both an enabler of financial inclusion and a potential source of algorithmic inequality. Drawing on cross-jurisdictional analysis from the European Union’s Artificial Intelligence Act to adaptive frameworks in Africa, Asia, and Latin America the study identifies how risk-based and principle-oriented governance models are evolving to balance innovation, fairness, and systemic stability. Empirical insights reveal that digital finance has significantly advanced global financial inclusion, particularly through mobile payments and AI-powered credit systems. However, challenges persist in ensuring ethical AI deployment, data transparency, and equitable access.

To address these tensions, the research proposes an Integrated Policy and Governance Model anchored in three dimensions: innovation enablement, inclusion promotion, and ethical responsibility. The model advances a five-pillar roadmap encompassing ethical AI standards, digital inclusion mandates, sustainability integration, adaptive regulatory infrastructures, and cross-border cooperation. Ultimately, the study underscores that the future of global finance depends not only on technological capability but on governance frameworks that embed fairness, accountability, and human-centered design.

“Learning from your neighbours”: Prudential provisions of the EU AI Act for the UK insurance supervisory regime.

2026-02-06T11:22:16+00:00

This paper focuses on the prudential regulation and supervision of UK re-insurance undertakings, in relation to Artificial Intelligence (AI) considerations. Specifically, it presents a critical analysis of the prudential provisions of the European Artificial Intelligence (AI) Act which could be adjusted and adopted in the UK regulatory and supervisory regime, in line with the Prudential Regulation Authority (PRA)’s approach to insurance supervision. Building on the gaps identified regarding the supervisory approach to AI applications within the insurance value chain, it presents proposed developments based on the EU AI Act. The purpose of this paper is to present a critique on the learnings from the EU AI Act in relation to risk management systems and risk management for UK financial regulators regarding the prudential supervision of re-insurers. These are linked to the assessment performed by the European Insurance and Occupational Pensions Authority (EIOPA) in relation to the governance and risk management of AI to ensure the appropriate regulation and supervision of the risks linked to re-insurance activities. Effectively capturing how this approach towards the prudent AI governance and risk management framework could be adopted by the PRA, and ultimately how prudential supervision should be adjusted to monitor AI applications and uses. Beyond the EU AI Act, the principles from the International Association of Insurance Supervisors (IAIS) in relation to risk management systems from a prudential angle are also discussed to complement the recommendations for UK regulators, in relation to risk management practices and the prudential regulatory expectations based on the PRA’s Rulebook, in combination with the Lloyd’s of London Principles for the London market. The focus is placed on the AI considerations within the Own Risk and Solvency Assessment, model risk management and stress testing, all interlinked core prudential components of Solvency II and Delegated Acts. This doctrinal legal research adopts a socio-legal methodology combined with economic theory in analysing the prudential regulatory frameworks underpinning AI. The economic analysis of law and regulation constitutes the methodological approach adopted to critically examine the prudential provisions of the EU AI Act applicable to re-insurers. The contribution of this paper is twofold, providing insights for advances to the (a) regulation and (b) supervision of AI applications within the insurance sector for the UK, based on the EU AI Act and EIOPA’s approach. Regulating and supervising AI applications within the UK insurance industry is of high importance, linked to AI uses and the inherent purpose of insurance. In particular referring to the growth and capacity of the insurance market, with wider applications of AI, and the insurability of risks, with the case of under-insurance and protection gap, towards affordability via increased accuracy of risks and improved underwriting, both outcomes of prudential activities. Overall, this research adds to the growing literature about regulatory implications from AI, using the UK insurance industry as a case study, commenting on the EU regulatory regime, from a prudential lens, on how this could be utilised to shape UK practice and policy.

The Role Of AI-Driven Financial Strategies in Enhancing Business Performance

2026-02-06T11:20:02+00:00

This study aims to test the development of performance of Artificial Intelligence in the UK FTSE 250 companies and FinTech companies. Also, pay attention to performance gains and the kind of AI devices that have been integrated, and the role played in operational efficiency and cost optimisation. The literature indicates that successful implementation of AI involves more than the implementation of technology. It is based on leadership commitment, change management, digital culture, and cross-functional collaboration. The study uses a secondary data methodology, where it uses company reports, industry reports and financial records to assess how AI apps lead to measuring business results. The findings indicate that Experian made performance and financial gains in efficiency and profitability regarding AI-powered model development and risk management ventures. However, Currys PLC made cost reduction and profitability boosts through Action AI and dynamic pricing systems. Revolut and Monzo were using AI to detect fraud and help in cost-efficiency with customer services, whereas Virgin Money used conversational AI to optimise service delivery. Keller Group showed how AI can improve decision-making as a governance practice. The research advises enhancing the leadership structures in place, incorporating a digital culture and making it scalable with ethics in mind in the long run.

The Fraud Detection Optimization in Open Metaverse Blockchain Transactions: Case study based on ML-GRU Neural Networks

2026-01-19T10:40:48+00:00

The study explores anomaly detection in blockchain transactions within the Open Metaverse Our proposed system aims to achieve three critical objectives: detecting fraudulent transactions by identifying suspicious patterns and anomalies, assessing transaction risks through the categorization of risk profiles, and analyzing user behavior to enhance security, personalize financial services, and improve user experiences. Through the meticulous classification of transactions for fraud detection, risk assessment, and user behavior analysis, this project aspires to bolster the security and transparency of Open Metaverse finance, setting the stage for a safer and more user-centric virtual financial landscape.

DATASET: -The dataset comprises 78,600 entries, each depicting a transaction within the metaverse. These entries are characterized by various attributes including the Timestamp, Hour of the Day, Sending and Receiving Addresses, Transaction Amount, Type, Location Region, and IP Prefix, along with user-centric data like Login Frequency, Session Duration, Purchase Patterns, Age Group, Risk Score, and potential Anomalies.

Bridging the Gap: Enhancing Traditional Auditing Techniques Using AI for Improved Audit Quality in the digital era

2026-01-19T10:43:32+00:00

Bridging the Gap: Enhancing Traditional Auditing Techniques Using AI for Improved Audit Quality in the digital era

Extended Abstract

In recent years, every facet of the business environment is experiencing a rapid technological mind shift, shedding the old ways of operations and embracing the new normal offered by technology (Popkova & Sergi, 2021). Artificial Intelligence (AI) has come to stay, as it has now been infused into the operations of several businesses to optimize profit, increase revenue, and reduce costs (Almufadda & Almezeini, 2021). The reporting aspect of business is not left out as AI is revolutionizing the traditional accounting process. Natural language processing, machine learning, big data, predictive analysis, and advanced accounting software has transformed the way financial information is processed (Mwachikoka, 2024). This is done by automating data collection, analysis, and report preparation, thereby enhancing the accuracy, timeliness, and reliability of financial information while reducing human intervention.

In today’s fast changing business environment, auditing remains essential in providing assurance and instilling trust in the financial statement (Vlaović-Begović & Tomašević, 2016; Fotoh & Lorentzon, 2023), as it tells how true and fair the financial statements are, as presented by the directors (IAASB 2024). For much of its history, auditing has relied on traditional methods such as sampling, substantive testing, analytical procedures, and professional judgment — all of which rely heavily on the auditor’s skill, expertise and intuition. These techniques have proven sufficient in traditional business environments. However, the world auditors operate in today has changed dramatically with technology. Organizations now generate and store vast amount of data across digital systems, and financial transactions occur in real time through complex, interconnected systems. This new digital reality exposes a fundamental tension between the constraints of traditional audit methods and the opportunities offered by emerging technologies (Usul & Alpay, 2024).

This article describes this issue as the audit technology assurance gap (ATAG). There is a growing disconnect between the demands of the digital business environment and the capacity of traditional auditing techniques to meet these demands (Usul & Alpay, 2024). This gap emerges in several forms. There is a gap of scale, as manual audit procedures can no longer keep up with the sheer volume and velocity of digital transactions being processed across global systems (Celestin & Vanitha, 2019; Al-Ateeq et al., 2022). There is also a gap of perception, where even the most skilled human auditors may overlook complex misstatements or subtle anomalies hidden within massive datasets (Celestin & Vanitha, 2019; Rahman et al., 2021). In the same vein, there is a gap of time, as traditional audits provide assurance based on past events — a snapshot of financial health at a particular moment, while stakeholders nowadays seek real-time insights into financial performance, emerging risks and financial integrity.

As financial reporting has therefore had to be more timely and transparent, therefore audit and assurance services are expected to adapt and likewise, evolve (Sewpersadh, 2025). However, the traditional audit model, when used in its basic form, struggles to meet the evolving expectations of these stakeholders (Usul & Alpay, 2024). Consequently, the auditing profession is at a critical point, requiring a modification of its existing methodologies to remain in tune with the digital transformation influencing other areas of business (Sewpersadh, 2025).

Although there is a growing body of literature exploring the relationship between AI and auditing, most of it remains conceptual, focusing on the technological advantages or potential of AI as it relates to auditing. That is, these articles focus on bridging the audit expectation gap by incorporating AI and other digital technologies in the audit process (Almufadda & Almezeini, 2021; Fotoh & Lorentzon, 2023; Mwachikoka, 2024). These studies focussed on how AI can automate audit tasks, detect anomalies, or enhance analytical precision. The practical aspect of examining how these technologies can be integrated to modify the traditional auditing procedures remains underexplored. The gap, which this study seeks to address is the ATAG, which is understanding how AI can complement traditional auditing techniques in the current real-world settings. This gap is significant because discussions around AI-assisted audit has to shift from abstract theorization to applied understanding. This article seeks to move the debate from “what AI can do” to “how AI can improve” the established audit framework to improve audit quality.

The aim of this article is to demonstrate how AI-assisted audit techniques could assist in bridging the audit technology assurance gap. The article will focus on practical terms, how transitioning from traditional auditing techniques to AI-assisted audit techniques can enhance audit quality by increasing efficiency, accuracy, and depth of analysis across the audit process. This discussion begins with a review of relevant theories to establish a strong theoretical background for understanding the subject matter. This study has a theoretical foundation on the Technology Acceptance Model (TAM), Sociotechnical Systems Theory (SST), and the Adaptive Structuration Theory (AST). A review of these theories should guide our understanding of how AI could be integrated to traditional audit techniques for improved audit quality in the digital era. It will then explore the audit process from a practical point of view to identify how it can be enhanced by AI integration. Subsequently, the article will examine the challenges of AI adoption in auditing. Thereafter, the article will conclude and propose recommendations towards having improved audit quality through AI assisted audit techniques.

Mapping Global Research on Financial Inclusion: A Bibliometric Analysis of Emerging Technologies, Policy Evolution, and Inclusive Innovation

2025-12-01T13:20:50+00:00

This study investigates how emerging technologies, evolving policy frameworks, and grassroots innovations are shaping the accessibility, inclusivity, and equity of financial services in the global context. Drawing on a bibliometric and science-mapping analysis of publications indexed in Scopus and Web of Science, the research examines the evolution of financial inclusion, its thematic structures, and its intellectual foundations. Using co-citation, co-word, and thematic evolution analyses supported by visualization tools such as VOSviewer and Biblioshiny, the study identifies key research clusters, influential contributors, and emerging conceptual linkages.

The findings reveal a significant expansion of financial inclusion research since 2010, characterized by a strong focus on technological enablers such as fintech, mobile money, blockchain, artificial intelligence, and central bank digital currencies. Concurrently, policy-oriented studies emphasize regulatory coherence, consumer protection, and cross-border governance, while socioeconomic investigations highlight persistent issues related to gender, rural access, and digital literacy. The thematic trajectory shows a shift from microfinance and access-based paradigms toward data-driven, sustainability-oriented, and ethically grounded financial ecosystems.

Overall, the study contributes to a deeper understanding of how global scholarship conceptualizes inclusive finance in the digital era, offering insights that inform future research, policy design, and innovation strategies aimed at achieving equitable and sustainable financial development.

Exploring the Role, Opportunities, and Challenges of crowdfunding adoption in developing the SMEs in Oman

2026-01-19T10:39:44+00:00

Extended Abstract

Previous studies on crowdfunding introduce three different research areas; The first group of studies focuses on examining general aspects of crowdfunding. The second trend of crowdfunding research has focused on reviewing and analyzing the prior studies of crowdfunding. The third group of studies focused on exploring the role and importance of crowdfunding to SMEs and entrepreneurs. Therefore, there is an extensive amount of literature in each of the areas of crowdfunding and SMEs. To the best of the researcher's knowledge, none of the prior studies investigated the role, opportunities, and challenges of crowdfunding adoption in the SMEs in Oman. Thus, the current project will fill this gap among SMEs in Oman.

To achieve this main objective, the qualitative interviews with the managers and CEO of the three crowdfunding companies in Oman is adopted. Furthermore, the collection of secondary data involved reviewing existing research, academic publications, and official reports from Omani and international organizations.

The research findings indicate that; 1) Crowdfunding platforms in Oman effectively address the financing gap for SMEs by offering flexible and innovative solutions. 2) Crowdfunding have witnessed rapid growth since 2022, funding 43 projects with a total of OMR 14.9 million by mid-2025. 3) The number of startups funded through crowdfunding platforms increased by over 87% in 2025. 4) Challenges of crowdfunding include weak awareness and understanding, difficulties in building trust, stringent regulatory requirements, a limited investor base and market size, economic impacts, and various technical and security issues. 5) The internal challenges include the lack of specialized expertise, ongoing technical needs for platform development, difficulty in quality control and risk management, significant regulatory burdens and compliance and reporting requirements, and financial and marketing challenges. 6) External challenges include regulatory constraints, complexities in investment-related legislation, a small market size with a limited investor base, weak public trust in alternative investment culture, regional and global competition, and adverse macroeconomic conditions. 7) The crowdfunding sector in Oman has promising growth opportunities, supported by government initiatives and Oman Vision 2040. 8) Cooperation between crowdfunding platforms in Oman and government entities can be fostered through joint financing programs, sharing credit data, and implementing training initiatives.

The study's relevance and motivations are derived from; firstly, the research area of crowdfunding is gaining global importance in research and practice, with its scope expanding over time. Secondly, the significant of Crowdfunding’ role in the economy and society is that they support SMEs and introduce new job opportunities. They are essential for many countries' economic development, making their presence a necessity. Thirdly, this study offers crucial insights for stakeholders on the role, opportunities, and challenges of crowdfunding adoption in the SMEs in Oman. Fourthly, empirical research in Oman lacks clear evidence on investigating the the role, opportunities, and challenges of crowdfunding adoption in the SMEs in Oman. Fifthly, this research aligns with the government's initiatives to fulfill Oman Vision 2040, focusing on innovation, sustainable financing, and the growth of the SME sector. Further, it introduces a significant contribution to the Crowdfunding literature. Finally, it raises awareness among SMEs and entrepreneurs about new funding opportunities.

This study's results benefit stakeholders, professional bodies, regulators, and policymakers in Oman, by providing real-time insights on the opportunities and challenges of Crowdfunding Growth in Oman.

The study suggests improving the effectiveness of crowdfunding platforms for SMEs in Oman through awareness campaigns, financial education, regulatory updates, strategic partnerships, financial incentives for investors, enhanced analytical and risk management capabilities, and regular performance disclosures showcasing success stories.

Designing Trust: A Correlational Study of UI Design Elements and AI Tool Features on Consumer Engagement in AI-Powered Banking Apps

2026-01-19T10:46:34+00:00

The rapid evolution of artificial intelligence (AI) has catalysed a transformative shift in the global banking landscape, with consumers increasingly turning to AI-powered applications for everyday financial management (Chukwudi et al., 2023). In response, fintech companies are intensifying efforts to enhance user experience through a seamless integration of intelligent functionalities and intuitive design. The intersection of user interface (UI) design and AI-driven personalisation has emerged as a critical determinant of user trust, satisfaction, and sustained engagement (‌Md Ashrafuzzaman et al, 2025). This study investigates the relationship between user interface design elements, such as colour palette, information density, and gamification, and AI-driven banking features, including savings recommendations, fraud alerts, and spending categorisation (Independent variable), to understand their combined impact on consumer engagement (dependent variable ) in AI-powered financial platforms.

Employing a mixed-methods design, the study combines quantitative user surveys with qualitative insights to assess engagement metrics (including session frequency, feature adoption, and duration of use) alongside perceptions of UI aesthetics and AI functionality. Statistical analyses, including correlation and regression modelling, will identify significant predictors of engagement. Meanwhile, open-ended responses will enrich the understanding of user trust, perceived value, and satisfaction. In conclusion, the results demonstrate that while UI design establishes the conditions for trust and ease of use, AI features provide sustained, functional value that drives consistent engagement. These findings highlight the importance of a dual-focus development strategy in fintech, one that equally prioritises intuitive, high-quality interface design and impactful, value-driven AI capabilities to cultivate strong and enduring consumer relationships.

In conclusion, the results demonstrate that while UI design establishes the conditions for trust and ease of use, AI features provide sustained, functional value that drives consistent engagement. These findings highlight the importance of a dual-focus development strategy in fintech, one that equally prioritises intuitive, high-quality interface design and impactful, value-driven AI capabilities to cultivate strong and enduring consumer relationships.

Volatility Clustering in Semiconductor Stock Returns: The Role of ChatGPT Inception, Version Upgrade, and the Launch of the DeepSeek AI Model — A Case Study on NVIDIA, AMD, and Intel

2026-02-06T11:19:29+00:00

ABSTRACT

This study investigates the impact of major artificial intelligence (AI) milestones, including the inception of ChatGPT (Nov 30, 2022), its subsequent upgrade (May 13, 2024), and the release of the DeepSeek AI model (Jan 20, 2025), on stock return volatility in the global semiconductor industry. Focusing on NVIDIA, AMD, and Intel, the research integrates event study methodology with GARCH-family models (GARCH, EGARCH, DCC-GARCH) to assess volatility clustering, asymmetric responses, and inter-firm spillover effects at the firm level.

Daily stock returns from January 2015 to March 2025 were analysed, with AI-related events categorised by type to capture differential market reactions. Results reveal pronounced volatility clustering in all three firms, with persistence levels highest for Intel. EGARCH estimates confirm asymmetric volatility, showing stronger market reactions to adverse AI-related news, particularly competitive threats such as DeepSeek’s entry. DCC-GARCH modelling indicates significant time-varying volatility spillovers, especially between NVIDIA and AMD, suggesting sector-wide contagion effects during AI innovation cycles.

The findings extend financial market literature by providing firm-level evidence on how AI-driven technological developments influence volatility dynamics within a strategically critical sector. The study offers actionable insights for investors, corporate strategists, and policymakers seeking to navigate innovation-induced risk, while demonstrating the methodological value of combining event study and advanced volatility models for high-tech market analysis.

Keywords: Artificial Intelligence, Volatility Clustering, Asymmetric Volatility, Spillover Effects, GARCH, EGARCH, DCC-GARCH, Event Study, Semiconductor Industry, NVIDIA, AMD, Intel.

Human Intellectual Humility: Addressing the fallibility of Artificial Enabled Systems

2026-01-19T10:40:22+00:00

The use of artificial intelligence (AI) cuts across diverse fields, allowing the generation of output at the speed of light. Despite its efficiency, AI is blamed for its hallucinations and biased output. While this is true, society is hypercritical of this anomaly, and they tend to forget the fallibility of human who trained the model. While studies have examined this problem from technical perspective, little is known about the influence of psychological factors on AI hallucination. Hence, from a psychological lens, this paper proposes intellectual humility to disrupt AI hallucinations. Qualitative research will be adopted to understand the development and application of AI in lived environments. AI developers and users will be recruited, and data will be collected in three stages using questions in the Comprehensive Intellectual Humility Scale (CIHS), behavioural semi-structured questionnaire and face-to-face interview. The findings of this research will highlight how intellectual humility shapes developers’ accountability of AI’s development and users’ responsibility for communicating true output from the AI system, challenging humans for AI hallucinations.

Fintech and adoption in modern banking

2025-12-01T13:37:42+00:00

ABSTRACT

Finance Technology (fintech) is changing banking, with the UK emerging as a global leader, but is not widely adopted among consumers or institutions. The aim of this dissertation is to assess the drivers, barriers and strategies informing the use of fintech in UK banking and to do this from the perspective of three main themes: consumer trust; capacity of institutions; and regulatory restrictions and implications.

Using an interpretivist philosophy, an original qualitative study is conducted through the lens of secondary research and qualitative data, and three UK fintech thematic sources (academic; industry; and regulatory) were synthesised through thematic analysis. The main findings demonstrate that consumers aged 18-34 adopted fintech primarily for the convenience and transparency, while older consumer groups were more cautious given concerns for fraud and lack of digital literacy concerning fintech applications. Institutions' adoption of fintech applications is problematic given the protracted costs of maintaining legacy systems, and identifying opportunities for innovation, however, also constrained to regulatory compliance. Regulation facilitates innovation, through open banking and the FCA sandbox, but also constrains smaller institutions through compliance obligations.

The value of this study is it extends existing theories on adoption to include institutional and regulatory factors and provides practical recommendations for the future of fintech development, that meets consumer needs, that is inclusive and is sustainable in a regulatory environment in the UK.

Exploring AI readiness in SMEs in Morocco: A qualitative study using Altimeter AI Maturity Model

2026-02-06T11:17:41+00:00

As Artificial Intelligence (AI) continues to transform industries, businesses are looking for structured frameworks to help them adopt to the new environment and integrate AI in their operations. For Small and Medium Enterprises (SMEs), adoption of AI could enhance productivity and efficiency. However, new technology adoption also requires human, technological, and financial resources that SMES often lack. This study uses the Altimeter’s AI Maturity Model, which outlines four sequential stages—Exploring, Experimenting, Formalizing, and Integrating to explore the extent to which SMEs in Morocco have adopted AI in their operations and their readiness to adopt AI. Semi-structured interviews will be conducted with ten SMEs’ owners in three different sectors, manufacturing, logistics, and hospitality sectors. The purpose is to determine SMEs’ readiness to adopt AI using the Altimeter’s AI Maturity Model and to identify enablers and barriers to future adoption. Findings of the study have theoretical and practical implications as they help reveal readiness factors specific to SMEs in a developing economy. For policy makers, findings of the study could guide policy makers in Morocco design effective strategies that would help with the diffusion of AI adoption in the economy.

Real-Time Fraud on Real-Time Rails: An AI “Smart Circuit Breaker” for Securing Instant Payments

2026-01-19T10:46:11+00:00

The launch of instant payment rails (RTP, FedNow) introduces a new, fundamental business risk: irrevocability. In this T+0, 24/7 world, the legacy T+1 security architectures that are built on static rules and batch processing are architecturally mismatched to manage this risk. Fraudulent payment is no longer an operational issue to be "fixed"; it is an immediate, irreversible financial loss.

This paper proposes that Artificial Intelligence is a viable path forward and introduces an AI-driven "smart circuit breaker" as a native component of the core payment flow, not a simple "bolt-on."

This model becomes feasible through the rich, structured data of ISO 20022, enabling real-time contextual analysis and anomaly detection before settlement. This is not just a technical upgrade; it forces boardroom-level discussions on strategic trade-offs:

Balancing customer friction from false positives.
Justifying the ROI on new data infrastructure.
Solving the "explainability" (XAI) hurdle for auditors.

The paper concludes that properly architected AI is not a cost center but a critical trust enabler—and a competitive advantage for secure, reliable instant payments.