Sökning: "Loan Applications"

Visar resultat 1 - 5 av 21 uppsatser innehållade orden Loan Applications.

  1. 1. Explainable Artificial Intelligence and its Applications in Behavioural Credit Scoring

    Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Robert Iain Salter; [2023]
    Nyckelord :Behavioural Credit Scoring; Deep Learning; Machine Learning; Long Short-Term Memory; Default Prediction;

    Sammanfattning : 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. 2. From Data to Decision: : Using Logistic Regression to Determine Creditworthiness

    Kandidat-uppsats, KTH/Matematisk statistik

    Författare :Joel Norling; Sami Abdu; [2023]
    Nyckelord :Bachelor Thesis; Scorecard modeling; Mathematical Statistics; Logistic Regression; Consumer Credits; Binning; Kandidatuppsats; Scorecard-modellering; Matematisk statistik; Logistisk regression; Konsumentkrediter; Binning;

    Sammanfattning : The development of scorecards for customer credit rating is a well-established field in the financial sector. The aim of this project, conducted in collaboration with a Swedish credit institute, was to develop a statistical model for predicting customer performance. LÄS MER

  4. 3. GAN-Based Counterfactual Explanation on Images

    Magister-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Ning Wang; [2023]
    Nyckelord :: Machine Learning; Counterfactual Explanation; GAN; DCGAN;

    Sammanfattning : Machine learning models are widely used in various industries. However, the black-box nature of the model limits users’ understanding and trust in its inner workings, and the interpretability of the model becomes critical. LÄS MER

  5. 4. Expect the Unexpected: Measuring Noise & Bias in the Credit Assessment Process

    Kandidat-uppsats, Lunds universitet/Företagsekonomiska institutionen

    Författare :Jacob Skoglund; Leonard Ekberg; Pontus Govenius; [2022]
    Nyckelord :mortgage; credit assessment; loan officer; decision-making; bias; noise; kreditgivningsprocess; kredithandläggare; beslutsfattande; Business and Economics;

    Sammanfattning : The purpose of the thesis is to measure how bias impacts loan officers’ decision-making upon assessing mortgage applications and the level of noise embedded within the process. Quantitative data were collected from 15 loan officers working at three different branches at Handelsbanken answering a questionnaire based on fictional mortgage applications. LÄS MER

  7. 5. Pricing collateralized loan obligation tranches using machine learning : Machine learning applied to financial data

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Marcus Enström; [2022]
    Nyckelord :Collateralized loan obligation; Machine learning; Artificial neural networks; Financial data; Ensemble methods; Collateralized loan obligation; Maskininlärning; Artificiella neurala nätverk; Finansiell data; Ensemblemetoder;

    Sammanfattning : Machine learning and neural networks have recently become very popular in a large category of domains, partly thanks to their ability to solve complex problems by finding patterns in data, but also due to an increase in computing power and data availability. Successful applications of machine learning include for example image classification, natural language processing, and product recommendation. LÄS MER