[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-118982-en":3,"doc-seo-118982-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},118982,4398048949847,"Eliana","https://ap-avatar.wpscdn.com/avatar/400002536579ef2da7f?_k=1778318612642679267",8,"Research & Report","Towards improving real-time credit card fraud detection using supervised machine learning models on big data","The primary objective of this study is to improve supervised machine learning models for real-time credit card fraud detection across multiple datasets. Credit card fraud is treated as a serious form of identity theft causing ongoing economic and financial losses for both financial institutions and consumers. As commerce increasingly relies on online services, fraud has grown in volume and complexity, with attackers creating fraudulent cards that closely resemble legitimate ones while continually refining tactics. Although mitigation measures exist, rising losses indicate a persistent need for more accurate real-time detection, especially when high-dimensional data degrades model performance. The study targets improved detection on big-data datasets using a design science research approach.","Towards improving real-time credit card fraud detection  \nusing supervised machine learning models on big data  \nMY Pitsane  \n [orcid.org 0000-0002-8389-1587](orcid.org 0000-0002-8389-1587)  \nDissertation accepted in fulfillment of the requirements for the degree  \nMaster of Science in Computer Science at the North-West University  \nSupervisor: Dr JJ Greeff  \nCo-supervisor: Dr TH Mogale  \nCo-supervisor: Prof JT Janse van Rensburg  \nGraduation: November/December 2023  \nDECLARATION  \nI, Malehlohonolo Yvonne Pitsane, declare that  \nTowards improving real-time credit card fraud detection using supervised machine learning models on big data  \nis my own work and that all the sources I have used or quoted have been indicated and acknowledged by means of complete references, and that this dissertation has not been previously submitted by me for a degree at any other university.  \nACKNOWLEDGEMENTS  \nFirstly, I would like to thank God Almighty Lord Jesus for everything that He has done for me. Thank you, God, for the wisdom, understanding and intelligence that you have blessed me with. Never could I have made it, without you. You made a way where there was no way, I don’t knowhow but You did. Not by might, not by power , by your Spirit , God. Thank you very much Lord foryour Grace upon my life.  \nI would like to thank my supervisors Dr Japie Greeff, Dr Hope Mogale and Prof JT Janse van Rensburg for everything that they have done for me. Thank you for all the mentoring, guidance, teachings, support, and wisdom shared. May the Lord Almighty bless you with many more years of success and prosperity. Thank you for choosing me to be your student, believing in me and trusting me with your time. Thank you for seeing potential in me and believing in my capabilities, capacity, and hard work.  \nI would like to thank my parents for all the love and support, my pillars of strength. Thank you for believing in me and always supporting me in everything I do. Not once in my life did you give upon me but always supported me and provided me with a helping hand. Thank you for raising me with all of the warrior traits that empowered me to be where I am today. Thank you very much, Mom and Dad. Thank you, Mom, for always reminding me to pray that there is nothing impossible with God and Thank you Dad for calls every day and being my number one academic supporter to check up on me and how my studies are going. Thank you, God , for my parents. I am blessed and highly favoured to still have both my parents to witness my academic journey.  \nI would like to thank my siblings for all their love and support. All of the lovely memories that they have provided me with which made every day of my life worth living. During the stressful times of my studies your love, jokes, and laughter helped me to push through the hard times knowing that I am loved.  \nI would like to thank my brother Sandile Mabuza for always being there for me and supporting me. Thank you, brother, for all the ice creams you always brought me and long serene drives to clear my mind-to feel better and gain strength and courage when the research was showing me flames. Thank you for always believing in me , that I could and would complete my studies no matter what, and that you would always be here for me and by my side when I need you. Thankyou for never giving up on me and always reminding me that I have potential and that I am able. If it was not because of your advice, encouraging words, love, care, and support - the journey would have been much more challenging. Thank you, brother.  \nLastly, I would like to thank myself for believing in me throughout my study journey. Thank you for never giving up no matter. Thank you , Malehlohonolo Pitsane , for never giving up on me. If it was not for you, the courage, motivation, and determination you had , I would not have completed this dissertation. Thank you for always igniting a fire inside of you. Never forget the motto that kept us going: where there is a","cbCaignxhac0E0Bt","https://ap.wps.com/l/cbCaignxhac0E0Bt","pdf",10497201,1,195,"English","en",105,"# Abstract\n## Problem background\n## Study objective\n## Challenges and motivation\n## Approach overview","[{\"question\":\"What is the primary objective of the study?\",\"answer\":\"To improve existing supervised machine learning models so they can detect credit card fraud in real time on multiple datasets.\"},{\"question\":\"Why is real-time credit card fraud detection needed?\",\"answer\":\"Because increasing online transactions and evolving attacker tactics have led to growing fraud activity and continuing financial losses despite existing measures.\"},{\"question\":\"What challenge affects machine learning performance in this context?\",\"answer\":\"Poor accuracy when dataset objects have high dimensionality.\"}]","Towards improving real-time credit card fraud detection using supervised machine learning models on big data | PDF",1785721354,491,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":28},"towards-improving-real-time-credit-card-fraud-detection-using-supervised-machine-learning-models-on-big-data","",{"@graph":36,"@context":86},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/towards-improving-real-time-credit-card-fraud-detection-using-supervised-machine-learning-models-on-big-data/118982/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04","2026-08-03",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What is the primary objective of the study?","Question",{"text":76,"@type":77},"To improve existing supervised machine learning models so they can detect credit card fraud in real time on multiple datasets.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"Why is real-time credit card fraud detection needed?",{"text":81,"@type":77},"Because increasing online transactions and evolving attacker tactics have led to growing fraud activity and continuing financial losses despite existing measures.",{"name":83,"@type":74,"acceptedAnswer":84},"What challenge affects machine learning performance in this context?",{"text":85,"@type":77},"Poor accuracy when dataset objects have high dimensionality.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":46,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":46,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":46,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":46,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]