[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126300-en":3,"doc-seo-126300-105":31,"detail-sidebar-cat-0-en-105":93},{"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":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},126300,2336475104957,"Seraphina","https://ap-avatar.wpscdn.com/avatar/22000c4c6bd8a5076e1?x-image-process=image/resize,m_fixed,w_180,h_180&k=1787554080175789136",8,"Research & Report","Peer-to-Peer Loan Default Detection using Machine Learning - Master Thesis","P2P lending platforms enable direct lending between borrowers and lenders, increasing exposure to loan default and the difficulty of assessing credit risk without financial intermediaries. This master thesis proposes a machine learning framework to improve the accuracy and interpretability of default predictions in P2P lending. Using the public Bondora dataset (2009–2023), it analyzes outliers, identifies key drivers of defaults, and addresses class imbalance through dedicated strategies. Traditional, ensemble, and neural models are compared, with AutoGluon and XGBoost showing the strongest performance.","Master's Degree Program in  \nData Science and Advanced Analytics  \nMDSAA  \nPeer-to-Peer Loan Default Detection using Machine Learning  \nSabeen Mubashar  \nMaster Thesis  \npresented as partial requirement for obtaining a Master’s Degree in Data Science and Advanced Analytics  \nNOVA Information Management School  \nInstituto Superior de Estatística e Gestão de Informação  \nUniversidade Nova de Lisboa  \nNOVA Information Management School Instituto Superior de Estatística e Gestão de Informação  \nUniversidade Nova de Lisboa  \nPeer-to-Peer Default Loan Detection using Machine Learning  \nby  \nSabeen Mubashar  \nMaster Thesis presented as partial requirement for obtaining the Master’s degree in Data Science and Advanced Analytics, specialising in Data Science.  \nSupervised by  \nProfessor Roberto Henriques  \nOctober, 2024  \nSTATEMENT OF INTEGRITY  \nI hereby declare having conducted this academic work with integrity. I confirm that I have not used plagiarism or any form of undue use of information or falsification of results along the process leading to its elaboration. I further declare that I have fully acknowledged the Rules of Conduct and Code of Honor from the NOVA Information Management School.  \nLisbon, April 2024  \nACKNOWLEDGEMENTS  \nFirst, I would like to express gratitude to those who have supported and guided me on this journey as my academic career ends.  \nI'd like to give special thanks to Professor Roberto, whose interest in machine learning inspired me greatly. His guidance, unwavering support, understanding, and ongoing feedback have been invaluable.  \nI would like to express my heartfelt thanks to my parents for their support and for enlightening my life by providing me with a good quality education and for standing behind me as a pillar of strength throughout my life. I am equally thankful to my siblings, who brighten up my world.  \nFurther, I want to acknowledge my friends, with whom this place has looked very much like a home away from home; your encouragement and presence have been a great comfort and motivation.  \nI am deeply grateful to each and every one of you.  \nABSTRACT  \nP2P lending platforms are responsible for direct lending between borrowers and lenders, avoiding the traditional intermediaries within the financial system. This exposes them to additional risk within the business space and the challenges in assessing loan risk that can result in financial loss. This study introduces a machine learning framework designed to enhance the accuracy and interpretability of default predictions in P2P lending. Based on the publicly available Bondora dataset (2009–2023), this research identifies outliers and key factors influencing loan defaults and explores strategies for handling data imbalance. Traditional, ensemble and neural network models are rigorously compared. AutoGloun, and XGBoost have emerged as top-performing models. The findings highlight that the proposed approach is reliable for the loan default prediction at the pre-approval stage, offering moderate accuracy while protecting investments and promoting platform stability. This paper, therefore, presents a comprehensive framework for tackling loan default risk in peer-to-peer lending by integrating predictive modelling and Explainable AI.  \nKEYWORDS  \nPeer-to-Peer lending, Loan Default Prediction, Machine Learning, Explainable AI (XAI), Imbalanced Data  \nTABLE OF CONTENTS  \n1. Introduction .................................................................................................................. 1  \n1.1. Bondora ................................................................................................................. 1  \n1.2. Thesis Objective.....................................................................................................3  \n1.3. Thesis Structure .....................................................................................................3  \n2. Literature review ....................................................","cbCaionxRhWcKfhB","https://ap.wps.com/l/cbCaionxRhWcKfhB","pdf",1904128,7,1,61,"English","en",105,"# Introduction\n## Bondora\n## Thesis Objective\n## Thesis Structure\n# Literature review\n# Methodology\n## Data Preparation\n## Data Imbalance Techniques\n## Modelling\n## Evaluation Metrics","[{\"question\":\"What problem does the thesis address in peer-to-peer lending?\",\"answer\":\"The thesis focuses on loan default risk and the challenge of accurately predicting defaults in P2P lending while keeping predictions interpretable.\"},{\"question\":\"Which dataset and time range are used for the research?\",\"answer\":\"The study uses the publicly available Bondora dataset covering 2009–2023.\"},{\"question\":\"How does the study handle imbalanced default data?\",\"answer\":\"It introduces and evaluates strategies for dealing with data imbalance so that models can learn effectively despite skewed classes.\"}]","Peer-to-Peer Loan Default Detection using Machine Learning - Master Thesis | PDF",1785904329,154,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":88,"head_meta":90,"extra_data":92,"updated_unix":29},"peer-to-peer-loan-default-detection-using-machine-learning-master-thesis","",{"@graph":37,"@context":87},[38,55,70],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,52],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":48},"https://docshare.wps.com/document/","Document",2,{"item":50,"name":12,"@type":44,"position":51},"https://docshare.wps.com/document/research-report/",3,{"item":53,"name":13,"@type":44,"position":54},"https://docshare.wps.com/document/peer-to-peer-loan-default-detection-using-machine-learning-master-thesis/126300/",4,{"url":53,"name":13,"@type":56,"author":57,"headline":13,"publisher":59,"fileFormat":62,"inLanguage":24,"description":14,"dateModified":63,"datePublished":64,"encodingFormat":62,"isAccessibleForFree":65,"interactionStatistic":66},"DigitalDocument",{"name":9,"@type":58},"Person",{"url":42,"name":60,"@type":61},"DocShare","Organization","application/pdf","2026-08-23","2026-08-05",true,{"@type":67,"interactionType":68,"userInteractionCount":20},"InteractionCounter",{"@type":69},"ViewAction",{"@type":71,"mainEntity":72},"FAQPage",[73,79,83],{"name":74,"@type":75,"acceptedAnswer":76},"What problem does the thesis address in peer-to-peer lending?","Question",{"text":77,"@type":78},"The thesis focuses on loan default risk and the challenge of accurately predicting defaults in P2P lending while keeping predictions interpretable.","Answer",{"name":80,"@type":75,"acceptedAnswer":81},"Which dataset and time range are used for the research?",{"text":82,"@type":78},"The study uses the publicly available Bondora dataset covering 2009–2023.",{"name":84,"@type":75,"acceptedAnswer":85},"How does the study handle imbalanced default data?",{"text":86,"@type":78},"It introduces and evaluates strategies for dealing with data imbalance so that models can learn effectively despite skewed classes.","https://schema.org",{"og:url":53,"og:type":89,"og:title":13,"og:site_name":60,"og:description":14},"article",{"robots":91,"canonical":53},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":94},[95,99,103,107,112,117,121,124,129,132,136],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":96,"show_sort_weight":97,"slug":98},"Story & Novel",90,"story-novel",{"id":48,"doc_module":4,"doc_module_name":47,"category_name":100,"show_sort_weight":101,"slug":102},"Literature",80,"literature",{"id":54,"doc_module":4,"doc_module_name":47,"category_name":104,"show_sort_weight":105,"slug":106},"Exam",70,"exam",{"id":108,"doc_module":4,"doc_module_name":47,"category_name":109,"show_sort_weight":110,"slug":111},5,"Comic",60,"comic",{"id":113,"doc_module":4,"doc_module_name":47,"category_name":114,"show_sort_weight":115,"slug":116},6,"Technology",50,"technology",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":118,"show_sort_weight":119,"slug":120},"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":47,"category_name":138,"show_sort_weight":108,"slug":139},19,"General","general"]