Essays about: "thesis in customer loan"

Showing result 1 - 5 of 12 essays containing the words thesis in customer loan.

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

    University essay from Stockholms universitet/Institutionen för data- och systemvetenskap

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

    Abstract : 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. READ MORE

  3. 2. Probability of Default Machine Learning Modeling : A Stress Testing Evaluation

    University essay from Umeå universitet/Institutionen för matematik och matematisk statistik

    Author : Tobias Andersson; Mattias Mentes; [2023]
    Keywords : Probability of Default; Machine Learning; Stress Testing; Logistic Regression; Decision Tree; Random Forest; Artificial Neural Network;

    Abstract : This thesis aims to assist in the development of machine learning models tailored for stress testing. The main objective is to create models that can predict loan defaults while considering the impact of macroeconomic stress. READ MORE

  4. 3. From Data to Decision: : Using Logistic Regression to Determine Creditworthiness

    University essay from KTH/Matematisk statistik

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

    Abstract : 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. READ MORE

  5. 4. Predicting Subprime Customers' Probability of Default Using Transaction and Debt Data from NPLs

    University essay from KTH/Matematisk statistik

    Author : Lai-Yan Wong; [2021]
    Keywords : Credit Scoring Model; Probability of Default; Payment Behaviour; Subprime Customer; Non-performing Loan; Logistic Regression; Regularization; Feature Selection; Kreditvärdighetsmodell; Sannolikhet för Fallissemang; Betalningsbeteende; Högriskkunder; Nödlidandelån; Logistik Regression; Regularisering; Variabelselektion;

    Abstract : This thesis aims to predict the probability of default (PD) of non-performing loan (NPL) customers using transaction and debt data, as a part of developing credit scoring model for Hoist Finance. Many NPL customers face financial exclusion due to default and therefore are considered as bad customers. READ MORE

  6. 5. Loss Given Default Estimation with Machine Learning Ensemble Methods

    University essay from KTH/Matematisk statistik

    Author : Elina Velka; [2020]
    Keywords : Loss Given Default; Non-Performing Loans; Internal Ratings Based Approach; Machine Learning; Decision Tree; Random Forest; Boosted Method; Förlust vid fallissemang; Icke-presterande lån; Intern riskklassificeringsmetod; Maskininlärning; Decision Tree; Random Forest; Boosted Metod;

    Abstract : This thesis evaluates the performance of three machine learning methods in prediction of the Loss Given Default (LGD). LGD can be seen as the opposite of the recovery rate, i.e. the ratio of an outstanding loan that the loan issuer would not be able to recover in case the customer would default. READ MORE