Essays about: "Credit validation"

Showing result 1 - 5 of 21 essays containing the words Credit validation.

  1. 1. Credit Card Approval Prediction : A comparative analysis between logistic regressionclassifier, random forest classifier, support vectorclassifier with ensemble bagging classifier.

    University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Author : Dhanush Janapareddy; Narendra Chowdary Yenduri; [2023]
    Keywords : Machine Learning; Logistic Regression; Random Forest; Support Vector Machine; Ensemble Learning Bagging.;

    Abstract : 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. READ MORE

  3. 2. Modeling Credit Default Swap Spreads with Transformers : A Thesis in collaboration with Handelsbanken

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Johan Luhr; [2023]
    Keywords : Machine Learning; Transformer; Finance; Credit Default Swap; Credit Valuation Adjustment; Time Series Data; Maskininlärning; Transformer; Finance; Kreditswapp; Kredit Värderings Justering; Tidsserie data;

    Abstract : In the aftermath of the credit crisis in 2007, the importance of Credit Valuation Adjustment (CVA) rose in the Over The Counter (OTC) derivative pricing process. One important part of the pricing process is to determine Probability of Defaults (PDs) of the counterparty in question. READ MORE

  4. 3. Evaluating Random Forest and k-Nearest Neighbour Algorithms on Real-Life Data Sets

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Atheer Salim; Milad Farahani; [2023]
    Keywords : Random Forest; k-Nearest Neighbour; Evaluation; Machine Learning; Classification; Execution Time; Slumpmässig Skog; k-Närmaste Granne; Utvärdering; Maskininlärning; Klassificiering; Exekveringstid;

    Abstract : 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. READ MORE

  5. 4. Credit Card Transaction Fraud Detection Using Neural Network Classifiers

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Ehsan Nazeriha; [2023]
    Keywords : GAN; Deep Learning; Variational Autoencoder; Anomaly Detection; SMOTE; GAN; Djupinlärning; Variational Autoencoder; Anomali detektering; SMOTE;

    Abstract : With increasing usage of credit card payments, credit card fraud has also been increasing. Therefore a fast and accurate fraud detection system is vital for the banks. To solve the problem of fraud detection, different machine learning classifiers have been designed and trained on a credit card transaction dataset. READ MORE

  6. 5. Capabilities and Processes to Mitigate Risks Associated with Machine Learning in Credit Scoring Systems : A Case Study at a Financial Technology Firm

    University essay from KTH/Skolan för industriell teknik och management (ITM)

    Author : Jakob Pehrson; Sara Lindstrand; [2022]
    Keywords : Trustworthy AI; Credit Scoring; Digital Capabilities; Fintech; Etisk AI; Kreditvärdighet; Digitala Förmågor; Fintech;

    Abstract : Artificial intelligence and machine learning has become an important part of society and today businesses compete in a new digital environment. However, scholars and regulators are concerned with these technologies' societal impact as their use does not come without risks, such as those stemming from transparency and accountability issues. READ MORE