Optimizing Revenue and Pricing on Upi Transaction Using Ai and Dynamic Pricing Models

Optimizing Revenue and Pricing on Upi Transaction Using Ai and Dynamic Pricing Models | 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 Optimizing Revenue and Pricing on Upi Transaction Using Ai and Dynamic Pricing Models Prema Kumari, Antony Raj This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6544016/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background : India’s Unified Payments Interface (UPI) has revolutionized global e-commerce by enabling seamless, low-cost, and real-time transactions. This study explores the integration of AI with a dynamic pricing optimization model to enhance revenue management (RM) and pricing strategies within UPI-driven transactions. Methods : We analyze UPI transaction data from 2021 to 2024, covering 13 billion transactions. A multi-disciplinary approach, integrating data analytics, consumer behavior, economics, and marketing, is employed. AI-driven predictive analytics are applied to identify key factors influencing Person-to-Merchant (P2M) dynamics, such as transaction reliability, merchant categories, regional factors, and fraud risks. A dynamic pricing model is proposed that adjusts prices based on these factors, with AI enhancing decision-making. Results : AI analysis reveals that reliable payments (40%), merchant categories (25%), and regional factors (20%) are the primary drivers of P2M growth. Fraud concerns (15%) impact pricing stability. The dynamic pricing model, incorporating transaction reliability, consumer sentiment from social media, and AI-driven fraud risk scores, is shown to optimize revenue. Groceries (2.32 billion transactions) and restaurants (1.25 billion) are leading categories, with urban areas dominating (65%). Conclusion : The study highlights the potential of AI in optimizing pricing, improving fraud detection, and fostering rural inclusion. Despite data limitations, these findings offer actionable insights for advancing sustainable e-commerce growth through UPI and AI-driven strategies. Unified Payments Interface (UPI) Dynamic Pricing AI Revenue Management Sustainable E-Commerce Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 25 Aug, 2025 Reviewers agreed at journal 28 Jun, 2025 Reviews received at journal 12 May, 2025 Reviewers agreed at journal 12 May, 2025 Reviewers agreed at journal 09 May, 2025 Reviewers invited by journal 02 May, 2025 Editor assigned by journal 30 Apr, 2025 Submission checks completed at journal 30 Apr, 2025 First submitted to journal 28 Apr, 2025 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. 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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-6544016","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":450961343,"identity":"8e5f2e8b-d435-4d01-ab3e-0a2463d928f5","order_by":0,"name":"Prema Kumari","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYPCCBBDBxpBwwAZIMzYeIFILM0hLGkhLAwlaGA4cBnPxajGXPnx0ww+GNHn+2eePPXhw5rzd2vbDQFtqbKJxabHsS0u72cOQYzjjXDK7QcKN28nbziQCtRxLy23AocXgDI/ZDR6GCsaGM8xsEgkfbiebHQBqYWw4jEcL/7ebfxgq7OdDtJxLNjv/kJAWHrbbPAw5iRvAWm4csDO7QcAWyx42s9syBmnJG88wm0kknElOMLsBtCUBj1/MeZif3XxTkWw77wzjM8kfx+zszc6nP3zwocYGt8OQSDBIBKtMwKEcTTEE2ONRPApGwSgYBSMUAABpuGXrnrT3hgAAAABJRU5ErkJggg==","orcid":"","institution":"SRM Institute of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Prema","middleName":"","lastName":"Kumari","suffix":""},{"id":450961344,"identity":"0899a960-d1f9-4a30-96b9-6c31d8f35aaa","order_by":1,"name":"Antony Raj","email":"","orcid":"","institution":"SRM Institute of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Antony","middleName":"","lastName":"Raj","suffix":""}],"badges":[],"createdAt":"2025-04-28 05:24:49","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6544016/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6544016/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82147117,"identity":"f0dc0a9f-9350-4469-b0f3-a0bdfd89cba9","added_by":"auto","created_at":"2025-05-07 06:59:03","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":281923,"visible":true,"origin":"","legend":"","description":"","filename":"3successbabyRPM.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6544016/v1_covered_433e328b-b074-4354-81b1-9383ab570ec8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eOptimizing Revenue and Pricing on Upi Transaction Using Ai and Dynamic Pricing Models\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-revenue-and-pricing-management","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Journal of Revenue and Pricing Management](https://www.palgrave.com/gp/journal/41272)","snPcode":"41272","submissionUrl":"https://submission.springernature.com/new-submission/41272/3","title":"Journal of Revenue and Pricing Management","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer SNAPPs","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Unified Payments Interface (UPI), Dynamic Pricing, AI, Revenue Management, Sustainable E-Commerce","lastPublishedDoi":"10.21203/rs.3.rs-6544016/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6544016/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: India’s Unified Payments Interface (UPI) has revolutionized global e-commerce by enabling seamless, low-cost, and real-time transactions. This study explores the integration of AI with a dynamic pricing optimization model to enhance revenue management (RM) and pricing strategies within UPI-driven transactions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: We analyze UPI transaction data from 2021 to 2024, covering 13 billion transactions. A multi-disciplinary approach, integrating data analytics, consumer behavior, economics, and marketing, is employed. AI-driven predictive analytics are applied to identify key factors influencing Person-to-Merchant (P2M) dynamics, such as transaction reliability, merchant categories, regional factors, and fraud risks. A dynamic pricing model is proposed that adjusts prices based on these\u003c/p\u003e\n\u003cp\u003efactors, with AI enhancing decision-making.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: AI analysis reveals that reliable payments (40%), merchant categories (25%), and regional factors (20%) are the primary drivers of P2M growth. Fraud concerns (15%) impact pricing stability. The dynamic pricing model, incorporating transaction reliability, consumer sentiment from social media, and AI-driven fraud risk scores, is shown to optimize revenue. Groceries (2.32 billion transactions) and restaurants (1.25 billion) are leading categories, with urban areas dominating (65%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: The study highlights the potential of AI in optimizing pricing, improving fraud detection, and fostering rural inclusion. Despite data limitations, these findings offer actionable insights for advancing sustainable e-commerce growth through UPI and AI-driven strategies.\u003c/p\u003e","manuscriptTitle":"Optimizing Revenue and Pricing on Upi Transaction Using Ai and Dynamic Pricing Models","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-07 06:50:54","doi":"10.21203/rs.3.rs-6544016/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-25T09:06:49+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"72310024796761013461508511672528614063","date":"2025-06-28T07:20:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-12T12:02:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"325358087507572435766035046617587025538","date":"2025-05-12T06:45:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"13298681570873054528772043472134637618","date":"2025-05-09T14:49:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-02T08:00:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-30T23:42:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-30T23:38:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Revenue and Pricing Management","date":"2025-04-28T05:20:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-revenue-and-pricing-management","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Journal of Revenue and Pricing Management](https://www.palgrave.com/gp/journal/41272)","snPcode":"41272","submissionUrl":"https://submission.springernature.com/new-submission/41272/3","title":"Journal of Revenue and Pricing Management","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer SNAPPs","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"3135a8e6-f9a7-444d-bba5-7778e882b546","owner":[],"postedDate":"May 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-10-03T08:08:07+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-07 06:50:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6544016","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6544016","identity":"rs-6544016","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}