Sökning: "credit evaluation"

Visar resultat 1 - 5 av 93 uppsatser innehållade orden credit evaluation.

  1. 1. Kreditgivningsprocess till SME : Vilken redovisningsinformation upplever banker behov av på grund av informationsasymmetri vid kreditgivning till SME?

    Kandidat-uppsats, Högskolan i Skövde/Institutionen för handel och företagande

    Författare :Biniam Zeru Tkue; Kristina Nedeljkovic; Sundus Jama; [2023]
    Nyckelord :SME; credit assessment process; information asymmetry; 5c-model; risk assessment; cash flow analysis; financial reporting information; SME; kreditbedömningsprocess; agentteori; 5c-modell; riskbedömning; kassaflödesanalys; redovisningsinformation;

    Sammanfattning : Bakgrund: SME (små och medelstora företag) spelar en avgörande roll för ekonomisk tillväxt och sysselsättning. Trots deras betydelse möter dessa företag ofta utmaningar när de försöker få tillgång till finansiering från banker. LÄS MER

  3. 2. Credit Exposure Modelling Using Differential Machine Learning

    Master-uppsats, Lunds universitet/Matematisk statistik

    Författare :Måns Karp; Samuel Wagner; [2023]
    Nyckelord :Counterparty credit risk; Differential machine learning; Exposure modelling; Heston model; Option pricing; Mathematics and Statistics;

    Sammanfattning : Exposure modelling is a critical aspect of managing counterparty credit risk, and banks worldwide invest significant time and computational resources in this task. One approach to modelling exposure involves pricing trades with a counterparty in numerous potential future market scenarios. LÄS MER

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

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

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

    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

  5. 4. An Evaluation of Leading Indicators in the Context of a Swedish Recession

    Master-uppsats, Lunds universitet/Nationalekonomiska institutionen

    Författare :Rami Soliman; [2023]
    Nyckelord :Probit; Financial Crisis; Recession; Sweden; Leading Indicators; Business and Economics;

    Sammanfattning : The aim of this paper is to evaluate potential leading indicators of a recession in Sweden. To answer the question potential leading indicators are first identified with previous findings in literature and with the current state of the Swedish financial system as background. LÄS MER

  7. 5. Peeking Through the Leaves : Improving Default Estimation with Machine Learning : A transparent approach using tree-based models

    Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik

    Författare :Elias Hadad; Angus Wigton; [2023]
    Nyckelord :Machine learning; Expected credit loss; Probability of default; ECL; PD; Risk Management; Credit Risk Management; Default Estimation; AI; Artificial intelligence; Fintech; Supervised learning; Decision tree; Random forest; XG boost; Transparency; Machine learning transparency;

    Sammanfattning : In recent years the development and implementation of AI and machine learning models has increased dramatically. The availability of quality data paving the way for sophisticated AI models. Financial institutions uses many models in their daily operations. LÄS MER