Keywords
explainable artificial intelligence
AI governance
Categories
How to Cite
Abstract
As financial systems get increasingly digitized, organizations are encountering increasingly high risks of algorithmic opacity, regulatory non-compliance, auditability gaps, and loss of institutional trust. Though artificial intelligence is now a mainstream instrument used in the assessment of financial risk, anomaly detection, and predictive analytics, its fast mainstreaming has also revealed structural vulnerabilities in governance arch design that is based on black-box models and automation-driven logic. These are the problems that highlight the increased significance of financial integrity systems that can entrench explainability, regulatory compliance, and human-centered oversight, as opposed to technology-based AI deployment strategies. This paper takes a governance-based approach to study the transformations occurring in transparency, risk containment, and integrity results in financial systems with the help of AI-enabled Financial Integrity Engines. The study, based on institutional economics and explainable AI theory, takes AI not as an independent decision-maker, but as an embedded governance mechanism, and the quality of which is determined by explainability, compliance-by-design, and human-in-the-loop control mechanisms.
References
Aljunaid, S.K.; Almheiri, S.J.; Dawood, H.; Khan, M.A. Secure and Transparent Banking: Explainable AI-Driven Federated Learning Model for Financial Fraud Detection. J. Risk Financial Manag. 2025, 18, 179. https://doi.org/10.3390/jrfm18040179
Bank for International Settlements (BIS). Sound Practices: Implications of Fintech Developments for Banks and Bank Supervisors. BIS Basel 2023. https://www.bis.org/bcbs/publ/d575.htm
Bouderhem, R. A Comprehensive Framework for Transparent and Explainable AI Sensors in Healthcare. Eng. Proc. 2024, 82, 49. https://doi.org/10.3390/ecsa-11-20524
Chen, P.; Wu, L.; Wang, L. AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications. Appl. Sci. 2023, 13, 10258. https://doi.org/10.3390/app131810258
Choowan, P.; Daovisan, H. Artificial Intelligence in Data Governance for Financial Decision-Making: A Systematic Review. Big Data Cogn. Comput. 2026, 10, 8. https://doi.org/10.3390/bdcc10010008
European Commission. Digital Economy and Society Index (DESI). European Union 2024. https://digital-strategy.ec.europa.eu/en/policies/desi
Financial Stability Board (FSB). Artificial Intelligence and Machine Learning in Financial Services. FSB 2023. https://www.fsb.org/2023/11/artificial-intelligence-and-machine-learning-in-financial-services/
Gunasekara, L.; El-Haber, N.; Nagpal, S.; Moraliyage, H.; Issadeen, Z.; Manic, M.; De Silva, D. A Systematic Review of Responsible Artificial Intelligence Principles and Practice. Appl. Syst. Innov. 2025, 8, 97. https://doi.org/10.3390/asi8040097
Hohma, E.; Lütge, C. From Trustworthy Principles to a Trustworthy Development Process: The Need and Elements of Trusted Development of AI Systems. AI 2023, 4, 904-925. https://doi.org/10.3390/ai4040046
International Monetary Fund (IMF). FinTech Notes and Artificial Intelligence in Financial Services Database. IMF 2024. https://www.imf.org/en/Topics/Fintech
Kafali, E.; Preuveneers, D.; Semertzidis, T.; Daras, P. Defending Against AI Threats with a User-Centric Trustworthiness Assessment Framework. Big Data Cogn. Comput. 2024, 8, 142. https://doi.org/10.3390/bdcc8110142
Lastrucci, A.; Pirrera, A.; Lepri, G.; Giansanti, D. Algorethics in Healthcare: Balancing Innovation and Integrity in AI Development. Algorithms 2024, 17, 432. https://doi.org/10.3390/a17100432
Mazur, V.; Koldovskyi, A.; Ryabushka, L.; Yakubovska, N. The Formation of a Rational Model of Management of the Construction Company’s Capital Structure. Financial and Credit Activity: Problems of Theory and Practice 2023, 6, 128–144. https://doi.org/10.55643/fcaptp.6.53.2023.4223
Organisation for Economic Co-operation and Development (OECD). Framework for the Classification of Artificial Intelligence Systems. OECD 2023. https://oecd.ai/en/classification
Organisation for Economic Co-operation and Development (OECD). OECD Artificial Intelligence Indicators. OECD 2024. https://oecd.ai/en/ai-indicators
Owens, E.; Sheehan, B.; Mullins, M.; Cunneen, M.; Ressel, J.; Castignani, G. Explainable Artificial Intelligence (XAI) in Insurance. Risks 2022, 10, 230. https://doi.org/10.3390/risks10120230
Prokopenko, O.; Chechel, A.; Koldovskiy, A.; Kldiashvili, M. Innovative Models of Green Entrepreneurship: Social Impact on Sustainable Development of Local Economies. Economics Ecology Socium 2024, 8, 89–111. https://doi.org/10.61954/2616-7107/2024.8.1-8
Rahman, M.M.; Pokharel, B.P.; Sayeed, S.A.; Bhowmik, S.K.; Kshetri, N.; Eashrak, N. riskAIchain: AI-Driven IT Infrastructure—Blockchain-Backed Approach for Enhanced Risk Management. Risks 2024, 12, 206. https://doi.org/10.3390/risks12120206
Ricciardi Celsi, L. The Dilemma of Rapid AI Advancements: Striking a Balance between Innovation and Regulation by Pursuing Risk-Aware Value Creation. Information 2023, 14, 645. https://doi.org/10.3390/info14120645
Rodríguez Valencia, L.; Ochoa Arellano, M.J.; Gutiérrez Figueroa, S.A.; Mur Nuño, C.; Monsalve Piqueras, B.; Corrales Paredes, A.d.V.; Bemposta Rosende, S.; López López, J.M.; Puertas Sanz, E.; Levi Alfaroviz, A. A Systematic Review of Artificial Intelligence Applied to Compliance: Fraud Detection in Cryptocurrency Transactions. J. Risk Financial Manag. 2025, 18, 612. https://doi.org/10.3390/jrfm18110612
Seralidou, E.; Kioskli, K.; Fotis, T.; Polemi, N. AI_TAF: A Human-Centric Trustworthiness Risk Assessment Framework for AI Systems. Computers 2025, 14, 243. https://doi.org/10.3390/computers14070243
Shaban, O.S.; Omoush, A. AI-Driven Financial Transparency and Corporate Governance: Enhancing Accounting Practices with Evidence from Jordan. Sustainability 2025, 17, 3818. https://doi.org/10.3390/su17093818
Sodnomdavaa, T.; Lkhagvadorj, G. Financial Statement Fraud Detection Through an Integrated Machine Learning and Explainable AI Framework. J. Risk Financial Manag. 2026, 19, 13. https://doi.org/10.3390/jrfm19010013
Stanford Institute for Human-Centered Artificial Intelligence. AI Index Report 2024. Stanford University 2024. https://aiindex.stanford.edu/report/
Thurzo, A. Provable AI Ethics and Explainability in Medical and Educational AI Agents: Trustworthy Ethical Firewall. Electronics 2025, 14, 1294. https://doi.org/10.3390/electronics14071294
Transparency International. Corruption Perceptions Index 2024. Transparency International 2024. https://www.transparency.org/en/cpi/2024
World Bank. World Development Indicators. World Bank DataBank 2024. https://databank.worldbank.org/source/world-development-indicators
World Bank. Worldwide Governance Indicators (WGI). World Bank Group 2024. https://www.worldbank.org/en/publication/worldwide-governance-indicators
Yaseen, H.; Al-Amarneh, A. Adoption of Artificial Intelligence-Driven Fraud Detection in Banking: The Role of Trust, Transparency, and Fairness Perception in Financial Institutions in the United Arab Emirates and Qatar. J. Risk Financial Manag. 2025, 18, 217. https://doi.org/10.3390/jrfm18040217
Yazdi, M.; Zarei, E.; Adumene, S.; Beheshti, A. Navigating the Power of Artificial Intelligence in Risk Management: A Comparative Analysis. Safety 2024, 10, 42. https://doi.org/10.3390/safety10020042
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