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This paper examines how artificial intelligence can be integrated into financial institutions using an enterprise architecture framework, focusing on three domains: risk management and fraud detection, personalized customer experiences, and automation of routine operations. Using a high-level analysis of how AI capabilities interact with enterprise architecture and compliance requirements, it identifies critical success factors for seamless integration with existing systems, including data governance, organizational readiness, and change management. A major limitation is that the work is a preprint and not peer reviewed, with the emphasis placed on proposing a framework rather than reporting new empirical results. This paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.
Abstract
This article examines the strategic integration of artificial intelligence within financial institutions through the lens of enterprise architecture. The article explores three key application domains: risk management and fraud detection, personalized customer experiences, and automation of routine operations. The article identifies critical success factors for seamless integration with existing systems while maintaining regulatory compliance by analyzing the interplay between AI capabilities and enterprise architecture frameworks. The article highlights how properly architected AI implementations can enhance security protocols, deliver personalized customer journeys, and optimize operational efficiency. This article contributes to both theoretical understanding and practical application by proposing a comprehensive framework that addresses implementation challenges, including data governance, organizational readiness, and change management. Financial institutions can utilize this framework to develop sustainable AI strategies that align with their broader digital transformation objectives while navigating the complex regulatory landscape of the financial services sector.
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ENTERPRISE ARCHITECTURE FOR AI INTEGRATION IN FINANCIAL SERVICES: A FRAMEWORK FOR RISK MANAGEMENT, CUSTOMER EXPERIENCE, AND OPERATIONAL EFFICIENCY | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 28 July 2025 V1 Latest version Share on ENTERPRISE ARCHITECTURE FOR AI INTEGRATION IN FINANCIAL SERVICES: A FRAMEWORK FOR RISK MANAGEMENT, CUSTOMER EXPERIENCE, AND OPERATIONAL EFFICIENCY Author : Sreenivasulu Gajula 0009-0002-0465-5218 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.175373301.12842125/v1 347 views 216 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract This article examines the strategic integration of artificial intelligence within financial institutions through the lens of enterprise architecture. The article explores three key application domains: risk management and fraud detection, personalized customer experiences, and automation of routine operations. The article identifies critical success factors for seamless integration with existing systems while maintaining regulatory compliance by analyzing the interplay between AI capabilities and enterprise architecture frameworks. The article highlights how properly architected AI implementations can enhance security protocols, deliver personalized customer journeys, and optimize operational efficiency. This article contributes to both theoretical understanding and practical application by proposing a comprehensive framework that addresses implementation challenges, including data governance, organizational readiness, and change management. Financial institutions can utilize this framework to develop sustainable AI strategies that align with their broader digital transformation objectives while navigating the complex regulatory landscape of the financial services sector. Supplementary Material File (fin_irjmets1742218681 3.pdf) Download 475.30 KB Information & Authors Information Version history V1 Version 1 28 July 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords artificial intelligence digital transformation enterprise architecture financial services risk management Authors Affiliations Sreenivasulu Gajula 0009-0002-0465-5218 [email protected] International Research Journal of Modernization in Engineering, Technology and Science Fidelity Investments View all articles by this author Metrics & Citations Metrics Article Usage 347 views 216 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Sreenivasulu Gajula. ENTERPRISE ARCHITECTURE FOR AI INTEGRATION IN FINANCIAL SERVICES: A FRAMEWORK FOR RISK MANAGEMENT, CUSTOMER EXPERIENCE, AND OPERATIONAL EFFICIENCY. Authorea . 28 July 2025. DOI: https://doi.org/10.22541/au.175373301.12842125/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. 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