Sökning: "credit card"
Visar resultat 1 - 5 av 74 uppsatser innehållade orden credit card.
1. Credit Card Fraud Detection by Nearest Neighbor Algorithms
Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaperSammanfattning : As the usage of internet banking and online purchases have increased dramatically in today’s world, the risk of fraudulent activities and the number of fraud cases are increasing day by day. The most frequent type of bank fraud in recent years is credit card fraud which leads to huge financial losses on a global level. LÄS MER
2. Explainable Artificial Intelligence and its Applications in Behavioural Credit Scoring
Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskapSammanfattning : Credit scoring is critical for banks to evaluate new loan applications and monitor existing customers. Machine learning has been extensively researched for this case; however, the adoption of machine learning methods is minimal in financial risk management. LÄS MER
3. Credit Card Approval Prediction : A comparative analysis between logistic regressionclassifier, random forest classifier, support vectorclassifier with ensemble bagging classifier.
Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskapSammanfattning : Background. Due to an increasing number of credit card defaulters, companies arenow taking greater precautions when approving credit applications. When a customermeets certain requirements, credit card firms typically use their experience todecide whether to grant them a credit card. LÄS MER
4. Betaltjänstlagen och konsumentskyddet - Kan farmor känna sig trygg när bedragaren varit framme?
Kandidat-uppsats, Lunds universitet/Juridiska institutionen; Lunds universitet/Juridiska fakultetenSammanfattning : För att öka användningen av digitala betaltjänster, såsom BankID, inom Europeiska unionen (EU) tillkom andra betaltjänstdirektivet (PSD2) år 2015. I Sverige implementerades PSD2 genom tillskottet av kapitel 5a i Lag (2010:751) om betaltjänster. LÄS MER
5. Evaluating Random Forest and k-Nearest Neighbour Algorithms on Real-Life Data Sets
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Computers can be used to classify various types of data, for example to filter email messages, detect computer viruses, detect diseases, etc. This thesis explores two classification algorithms, random forest and k-nearest neighbour, to understand how accurately and how quickly they classify data. LÄS MER