Design Principles for AI-Enhanced Process Automation: An eDSR Approach to Intelligent Data Validation in Financial Decisions

Design Principles for AI-Enhanced Process Automation: An eDSR Approach to Intelligent Data Validation in Financial Decisions | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Design Principles for AI-Enhanced Process Automation: An eDSR Approach to Intelligent Data Validation in Financial Decisions Damian Kedziora, Piotr Marciniak This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7206919/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Over the past decade, automation of business processes has been evolving onto more advanced and intelligent solutions that go beyond basic capabilities of rule-based robotization. This paper presents a Design Science Research (DSR) study conducted to develop and evaluate design principles for integrating fuzzy logic algorithms with Robotic Process Automation (RPA) to address complex data validation challenges in financial services. Following the echelon-based Design Science Research (eDSR) methodology, we decompose the design process into three interconnected echelons: problem diagnosis, solution design, as well as demonstration and evaluation. Our research addresses the gap in prescriptive knowledge for designing intelligent automation systems that can handle imperfect data matching scenarios while maintaining accuracy and compliance standards. The iterative research process conducted at a multinational IT corporation, enabled us to develop design principles guiding the integration of Jaro-Winkler, Levenshtein, and N-gram algorithms within RPA, resulting in a solution that achieved a 67% reduction in false rejection rates while maintaining 97% accuracy in data validation processes. Our main contributions include: ( 1 ) prescriptive design knowledge for enhancing RPA with fuzzy logic capabilities, ( 2 ) validated design principles for balancing automation flexibility with risk management in financial contexts, and ( 3 ) empirical evidence implementing Task-Technology Fit (TTF) theory at intelligent automation contexts. It provides actionable guidance for practitioners implementing AI-enhanced automation in complex, regulated environments. Intelligent Automation Fuzzy Logic Design Science Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7206919","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":492512358,"identity":"876b7e03-0aa3-4bca-88f6-024f67efe5bd","order_by":0,"name":"Damian Kedziora","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIie3OIQvCQBTA8QcDLXPWW1C/wsnANPSrbBiWDo2CQdNZFKsf48BiMLyxYHCwuqgItsGMgoLn0GDwhs1wfy7cHffjHYBO949hsYACeMWmaT1vR/QH4lTAAIhLCLzJM58XRCGs3d7H6wacejU44mXbDTgZIODwO7FjJsJFDB17fvDC1bnPOOnL2YqPUWQCaxxcmnoYmWgUxMhVJMlEeJekl/pTSSZBpXRKykQkp3SofClJ5JUSO81E1ODEIfEZwhXu2tw8UVQRK2HrS8bd9nIWnPIcx6161T8e8PadvCKfRywFOp1Op1P2AOIeWv87BKWoAAAAAElFTkSuQmCC","orcid":"","institution":"Lappeenranta University of Technology","correspondingAuthor":true,"prefix":"","firstName":"Damian","middleName":"","lastName":"Kedziora","suffix":""},{"id":492512359,"identity":"0a8dc38f-1893-4a73-87ae-953c8051f1e5","order_by":1,"name":"Piotr Marciniak","email":"","orcid":"","institution":"Lodz University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Piotr","middleName":"","lastName":"Marciniak","suffix":""}],"badges":[],"createdAt":"2025-07-24 15:08:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7206919/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7206919/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":94489396,"identity":"428195bf-7970-44f4-b1e3-af0c26d871af","added_by":"auto","created_at":"2025-10-27 17:04:30","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":535617,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7206919/v1_covered_c5533135-8c61-499a-b714-1d4e41fd0a2c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Design Principles for AI-Enhanced Process Automation: An eDSR Approach to Intelligent Data Validation in Financial Decisions","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Intelligent, Automation, Fuzzy, Logic, Design, Science","lastPublishedDoi":"10.21203/rs.3.rs-7206919/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7206919/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOver the past decade, automation of business processes has been evolving onto more advanced and intelligent solutions that go beyond basic capabilities of rule-based robotization. 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