Essays about: "credit risk of banking"

Showing result 1 - 5 of 73 essays containing the words credit risk of banking.

  1. 1. Credit Card Fraud Detection by Nearest Neighbor Algorithms

    University essay from Göteborgs universitet/Institutionen för matematiska vetenskaper

    Author : Ramin Maghsood; [2023-04-13]
    Keywords : Fraud; Bank Fraud; Credit Card Fraud; Fraud Detection; Nearest Neighbor Algorithms;

    Abstract : 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. READ MORE

  3. 2. Increasing explainability of neural network based retail credit risk models

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

    Author : Anton Evilevitch; [2023]
    Keywords : Explainability; Artificial Neural Network; Mortgage Credit Risk Modeling; Förklarbarhet; Artificiella Neurala Nätverk; Modellering av Hypotekskreditrisk;

    Abstract : Due to their ’black box’ nature, Artificial Neural Networks (ANN) are not permitted for use in various applications. One such application is mortgage credit risk modeling. READ MORE

  4. 3. Moral Hazard and Banking Risk, a Euro Area Analysis

    University essay from Lunds universitet/Nationalekonomiska institutionen

    Author : Emanuel Skeppås; [2023]
    Keywords : Moral Hazard; Capital regulation; Risk; Ownership Influence; Bank Charter; Profitability; Business and Economics;

    Abstract : The study investigates the effects of capital regulations on risk-taking within the Euro- zone banking sector from 2013 to 2019, specifically focusing on the impact of moral hazard stemming from bank charter value and ownership influence. Previous research suggests both bank charters and ownership influence can prompt different risk behaviours and po- tentially influence the effectiveness of capital regulations. READ MORE

  5. 4. RNN-based Graph Neural Network for Credit Load Application leveraging Rejected Customer Cases

    University essay from Högskolan i Halmstad/Akademin för informationsteknologi

    Author : Oskar Nilsson; Benjamin Lilje; [2023]
    Keywords : Machine Learning; Deep Learning; Reject Inference; GNN; GCN; Graph Neural Networks; RNN; Recursive Neural Network; LSTM; Semi-Supervised Learning; Encoding; Decoding; Feature Elimination;

    Abstract : Machine learning plays a vital role in preventing financial losses within the banking industry, and still, a lot of state of the art and industry-standard approaches within the field neglect rejected customer information and the potential information that they hold to detect similar risk behavior.This thesis explores the possibility of including this information during training and utilizing transactional history through an LSTM to improve the detection of defaults. READ MORE

  6. 5. Economic Capital Models : Methods for fitting loss distributions

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

    Author : William Fritzell; [2023]
    Keywords : Economic Capital; Distribution fitting; MCMC;

    Abstract : The thesis provides a well-researched classical approach to fit and predict the losses (extreme) for Lloyds Bank’s Dutch mortgage portfolio, their defaulted Dutch mortgage portfolio, and their German personal and car loan portfolio. This is a crucial piece for quantification of the economic loss, required for effective credit risk management by the Bank. READ MORE